diff --git a/.gitignore b/.gitignore index ed34a6e..cd08f88 100644 --- a/.gitignore +++ b/.gitignore @@ -161,4 +161,5 @@ cython_debug/ reformat.py Test.ipynb -create_collections.py \ No newline at end of file +create_collections.py +datasets \ No newline at end of file diff --git a/import-metadata.ipynb b/import-metadata.ipynb new file mode 100644 index 0000000..4201e56 --- /dev/null +++ b/import-metadata.ipynb @@ -0,0 +1,532 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "5f5d15bc-07b5-4931-9270-40bac400475d", + "metadata": {}, + "outputs": [], + "source": [ + "import frontmatter\n", + "import glob\n", + "import re\n", + "from pystac_client import Client\n", + "import json\n", + "from collections import OrderedDict\n", + "\n", + "import requests\n", + "from cognito_client import CognitoClient" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "a10fca2b-ad18-4aa3-988c-9fdb3f2ae226", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['campfire-lst-night-diff',\n", + " 'OMI_trno2-COG',\n", + " 'lis-global-da-tws',\n", + " 'EPA-annual-emissions_1B2b_Natural_Gas_Processing',\n", + " 'grdi-shdi-raster',\n", + " 'conus-reach',\n", + " 'EPA-annual-emissions_1B1a_Coal_Mining_Underground',\n", + " 'hls-entropy-difference',\n", + " 'snow-projections-median-585',\n", + " 'social-vulnerability-index-socioeconomic',\n", + " 'EPA-annual-emissions_4B_Manure_Management',\n", + " 'geoglam',\n", + " 'OMSO2PCA-COG',\n", + " 'lis-global-da-tws-trend',\n", + " 'EPA-annual-emissions_2B5_Petrochemical_Production',\n", + " 'EPA-annual-emissions_1B2b_Natural_Gas_Production',\n", + " 'facebook_population_density',\n", + " 'lis-tws-nonstationarity-index',\n", + " 'social-vulnerability-index-overall',\n", + " 'grdi-v1-raster',\n", + " 'EPA-annual-emissions_6A_Landfills_Industrial',\n", + " 'EPA-annual-emissions_6B_Wastewater_Treatment_Domestic',\n", + " 'snow-projections-median-245',\n", + " 'landfill-emit',\n", + " 'EPA-annual-emissions_6D_Composting',\n", + " 'ecco-surface-height-change',\n", + " 'hls-l30-002-ej-reprocessed',\n", + " 'houston-aod',\n", + " 'darnah-flood',\n", + " 'IS2SITMOGR4-cog',\n", + " 'hls-bais2-v2',\n", + " 'lis-global-da-swe',\n", + " 'EPA-annual-emissions_2C2_Ferroalloy_Production',\n", + " 'campfire-ndvi-diff',\n", + " 'lis-global-da-gpp-trend',\n", + " 'EPA-annual-emissions_4A_Enteric_Fermentation',\n", + " 'barc-thomasfire',\n", + " 'nightlights-hd-1band',\n", + " 'grdi-cdr-raster',\n", + " 'lis-global-da-gpp',\n", + " 'lis-global-da-evap',\n", + " 'houston-lst-day',\n", + " 'landsat-c2l2-sr-antarctic-glaciers-pine-island',\n", + " 'darnah-gpm-daily',\n", + " 'EPA-monthly-emissions_1B2b_Natural_Gas_Production',\n", + " 'lis-global-da-qs',\n", + " 'lis-global-da-qsb',\n", + " 'blue-tarp-planetscope',\n", + " 'landsat-c2l2-sr-lakes-aral-sea',\n", + " 'damage_probability_2022-10-03',\n", + " 'caldor-fire-burn-severity',\n", + " 'houston-lst-diff',\n", + " 'co2-mean',\n", + " 'nceo_africa_2017',\n", + " 'grdi-vnl-slope-raster',\n", + " 'landsat-c2l2-sr-lakes-tonle-sap',\n", + " 'disalexi-etsuppression',\n", + " 'social-vulnerability-index-overall-nopop',\n", + " 'houston-aod-diff',\n", + " 'EPA-monthly-emissions_1A_Combustion_Stationary',\n", + " 'nightlights-hd-monthly',\n", + " 'social-vulnerability-index-household-nopop',\n", + " 'EPA-daily-emissions_5_Forest_Fires',\n", + " 'EPA-annual-emissions_6A_Landfills_Municipal',\n", + " 'houston-landcover',\n", + " 'frp-max-thomasfire',\n", + " 'social-vulnerability-index-minority',\n", + " 'grdi-imr-raster',\n", + " 'landsat-c2l2-sr-lakes-lake-balaton',\n", + " 'landsat-nighttime-thermal',\n", + " 'EPA-annual-emissions_1B2b_Natural_Gas_Transmission',\n", + " 'lis-global-da-totalprecip',\n", + " 'EPA-annual-emissions_6B_Wastewater_Treatment_Industrial',\n", + " 'lis-tws-anomaly',\n", + " 'EPA-annual-emissions_1B2a_Petroleum',\n", + " 'EPA-monthly-emissions_4F_Field_Burning',\n", + " 'climdex-tmaxxf-access-cm2-ssp585',\n", + " 'CMIP585-winter-median-ta',\n", + " 'EPA-annual-emissions_5_Forest_Fires',\n", + " 'grdi-vnl-raster',\n", + " 'snow-projections-diff-245',\n", + " 'campfire-nlcd',\n", + " 'EPA-annual-emissions_1B2b_Natural_Gas_Distribution',\n", + " 'snow-projections-diff-585',\n", + " 'houston-ndvi',\n", + " 'eis_fire_perimeter',\n", + " 'CMIP245-winter-median-ta',\n", + " 'climdex-tmaxxf-access-cm2-ssp245',\n", + " 'campfire-albedo-wsa-diff',\n", + " 'houston-lst-night',\n", + " 'co2-diff',\n", + " 'blue-tarp-detection',\n", + " 'lis-etsuppression',\n", + " 'EPA-annual-emissions_1B1a_Coal_Mining_Surface',\n", + " 'caldor-fire-behavior',\n", + " 'lis-tvegsuppression',\n", + " 'modis-annual-lai-2003-2020',\n", + " 'EPA-annual-emissions_1A_Combustion_Mobile',\n", + " 'hls-s30-002-ej-reprocessed',\n", + " 'EPA-monthly-emissions_4B_Manure_Management',\n", + " 'lis-global-da-streamflow',\n", + " 'houston-urbanization',\n", + " 'social-vulnerability-index-housing',\n", + " 'hls-ndvi',\n", + " 'landsat-c2l2-sr-lakes-vanern',\n", + " 'lis-global-da-gws',\n", + " 'no2-monthly-diff',\n", + " 'CMIP245-winter-median-pr',\n", + " 'EPA-annual-emissions_1A_Combustion_Stationary',\n", + " 'climdex-tmaxxf-access-cm2-ssp126',\n", + " 'social-vulnerability-index-socioeconomic-nopop',\n", + " 'landsat-c2l2-sr-antarctic-glaciers-thwaites',\n", + " 'bangladesh-landcover-2001-2020',\n", + " 'mtbs-burn-severity',\n", + " 'climdex-tmaxxf-access-cm2-ssp370',\n", + " 'EPA-annual-emissions_4C_Rice_Cultivation',\n", + " 'landsat-c2l2-sr-lakes-lake-biwa',\n", + " 'nldas3',\n", + " 'nldas2',\n", + " 'EPA-monthly-emissions_1B2a_Petroleum',\n", + " 'MO_NPP_npp_vgpm',\n", + " 'hls-ndvi-difference',\n", + " 'fldas-soil-moisture-anomalies',\n", + " 'EPA-annual-emissions_1B1a_Abandoned_Coal',\n", + " 'no2-monthly',\n", + " 'oco2-geos-l3-daily',\n", + " 'social-vulnerability-index-housing-nopop',\n", + " 'lis-tws-trend',\n", + " 'sport-lis-vsm0_100cm-percentile',\n", + " 'EPA-monthly-emissions_4C_Rice_Cultivation',\n", + " 'social-vulnerability-index-minority-nopop',\n", + " 'social-vulnerability-index-household',\n", + " 'grdi-filled-missing-values-count',\n", + " 'hls-swir-falsecolor-composite',\n", + " 'combined_CMIP6_daily_GISS-E2-1-G_tas_kerchunk_DEMO',\n", + " 'grdi-v1-built',\n", + " 'EPA-annual-emissions_4F_Field_Burning',\n", + " 'campfire-lst-day-diff',\n", + " 'CMIP585-winter-median-pr']" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "collection_ids = [i.split(\"/\")[-1].split(\".\")[0] for i in glob.glob('ingestion-data//production/collections/*.json')]\n", + "collection_ids" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "f2a88c41-0b8d-4d9c-9014-31417bcc646e", + "metadata": {}, + "outputs": [], + "source": [ + "dataset_paths = glob.glob('datasets/*.mdx')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "3663c351-3ef0-45e9-bc99-71c3b1a3ae13", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "writing file: ingestion_data/collections_new_metadata/barc-thomasfire\n", + "writing file: ingestion_data/collections_new_metadata/eis_fire_perimeter\n", + "writing file: ingestion_data/collections_new_metadata/houston-ndvi\n", + "writing file: ingestion_data/collections_new_metadata/houston-lst-night\n", + "writing file: ingestion_data/collections_new_metadata/houston-lst-day\n", + "writing file: ingestion_data/collections_new_metadata/houston-landcover\n", + "writing file: ingestion_data/collections_new_metadata/houston-lst-diff\n", + "writing file: ingestion_data/collections_new_metadata/conus-reach\n", + "writing file: ingestion_data/collections_new_metadata/social-vulnerability-index-socioeconomic\n", + "writing file: ingestion_data/collections_new_metadata/social-vulnerability-index-socioeconomic-nopop\n", + "writing file: ingestion_data/collections_new_metadata/ecco-surface-height-change\n", + "writing file: ingestion_data/collections_new_metadata/mtbs-burn-severity\n", + "writing file: ingestion_data/collections_new_metadata/hls-bais2-v2\n", + "writing file: ingestion_data/collections_new_metadata/hls-swir-falsecolor-composite\n", + "writing file: ingestion_data/collections_new_metadata/landsat-nighttime-thermal\n", + "writing file: ingestion_data/collections_new_metadata/campfire-ndvi-diff\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_4B_Manure_Management\n", + "writing file: ingestion_data/collections_new_metadata/EPA-monthly-emissions_4B_Manure_Management\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_4C_Rice_Cultivation\n", + "writing file: ingestion_data/collections_new_metadata/EPA-monthly-emissions_4C_Rice_Cultivation\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_4A_Enteric_Fermentation\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_4F_Field_Burning\n", + "writing file: ingestion_data/collections_new_metadata/EPA-monthly-emissions_4F_Field_Burning\n", + "writing file: ingestion_data/collections_new_metadata/IS2SITMOGR4-cog\n", + "writing file: ingestion_data/collections_new_metadata/lis-etsuppression\n", + "writing file: ingestion_data/collections_new_metadata/mtbs-burn-severity\n", + "writing file: ingestion_data/collections_new_metadata/fldas-soil-moisture-anomalies\n", + "writing file: ingestion_data/collections_new_metadata/disalexi-etsuppression\n", + "writing file: ingestion_data/collections_new_metadata/mtbs-burn-severity\n", + "writing file: ingestion_data/collections_new_metadata/CMIP245-winter-median-pr\n", + "writing file: ingestion_data/collections_new_metadata/CMIP585-winter-median-pr\n", + "writing file: ingestion_data/collections_new_metadata/lis-global-da-evap\n", + "writing file: ingestion_data/collections_new_metadata/lis-global-da-gpp\n", + "writing file: ingestion_data/collections_new_metadata/lis-global-da-gws\n", + "writing file: ingestion_data/collections_new_metadata/lis-global-da-swe\n", + "writing file: ingestion_data/collections_new_metadata/lis-global-da-streamflow\n", + "writing file: ingestion_data/collections_new_metadata/lis-global-da-qs\n", + "writing file: ingestion_data/collections_new_metadata/lis-global-da-qsb\n", + "writing file: ingestion_data/collections_new_metadata/lis-global-da-tws\n", + "writing file: ingestion_data/collections_new_metadata/lis-global-da-totalprecip\n", + "writing file: ingestion_data/collections_new_metadata/houston-urbanization\n", + "writing file: ingestion_data/collections_new_metadata/hls-l30-002-ej-reprocessed\n", + "writing file: ingestion_data/collections_new_metadata/hls-s30-002-ej-reprocessed\n", + "writing file: ingestion_data/collections_new_metadata/social-vulnerability-index-housing\n", + "writing file: ingestion_data/collections_new_metadata/social-vulnerability-index-housing-nopop\n", + "writing file: ingestion_data/collections_new_metadata/nightlights-hd-1band\n", + "writing file: ingestion_data/collections_new_metadata/snow-projections-median-245\n", + "writing file: ingestion_data/collections_new_metadata/snow-projections-median-585\n", + "writing file: ingestion_data/collections_new_metadata/combined_CMIP6_daily_GISS-E2-1-G_tas_kerchunk_DEMO\n", + "writing file: ingestion_data/collections_new_metadata/OMSO2PCA-COG\n", + "writing file: ingestion_data/collections_new_metadata/geoglam\n", + "writing file: ingestion_data/collections_new_metadata/campfire-lst-day-diff\n", + "writing file: ingestion_data/collections_new_metadata/darnah-flood\n", + "writing file: ingestion_data/collections_new_metadata/darnah-gpm-daily\n", + "writing file: ingestion_data/collections_new_metadata/houston-aod-diff\n", + "writing file: ingestion_data/collections_new_metadata/frp-max-thomasfire\n", + "writing file: ingestion_data/collections_new_metadata/barc-thomasfire\n", + "writing file: ingestion_data/collections_new_metadata/damage_probability_2022-10-03\n", + "writing file: ingestion_data/collections_new_metadata/social-vulnerability-index-household\n", + "writing file: ingestion_data/collections_new_metadata/social-vulnerability-index-household-nopop\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_2B5_Petrochemical_Production\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_2C2_Ferroalloy_Production\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_1A_Combustion_Mobile\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_1A_Combustion_Stationary\n", + "writing file: ingestion_data/collections_new_metadata/EPA-monthly-emissions_1A_Combustion_Stationary\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_5_Forest_Fires\n", + "writing file: ingestion_data/collections_new_metadata/EPA-daily-emissions_5_Forest_Fires\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_1B1a_Coal_Mining_Underground\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_1B1a_Coal_Mining_Surface\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_1B1a_Abandoned_Coal\n", + "writing file: ingestion_data/collections_new_metadata/social-vulnerability-index-minority\n", + "writing file: ingestion_data/collections_new_metadata/social-vulnerability-index-minority-nopop\n", + "writing file: ingestion_data/collections_new_metadata/no2-monthly\n", + "writing file: ingestion_data/collections_new_metadata/no2-monthly-diff\n", + "writing file: ingestion_data/collections_new_metadata/OMI_trno2-COG\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_1B2a_Petroleum\n", + "writing file: ingestion_data/collections_new_metadata/EPA-monthly-emissions_1B2a_Petroleum\n", + "writing file: ingestion_data/collections_new_metadata/campfire-lst-night-diff\n", + "writing file: ingestion_data/collections_new_metadata/blue-tarp-detection\n", + "writing file: ingestion_data/collections_new_metadata/blue-tarp-planetscope\n", + "writing file: ingestion_data/collections_new_metadata/MO_NPP_npp_vgpm\n", + "writing file: ingestion_data/collections_new_metadata/co2-mean\n", + "writing file: ingestion_data/collections_new_metadata/co2-diff\n", + "writing file: ingestion_data/collections_new_metadata/landfill-emit\n", + "writing file: ingestion_data/collections_new_metadata/grdi-cdr-raster\n", + "writing file: ingestion_data/collections_new_metadata/grdi-filled-missing-values-count\n", + "writing file: ingestion_data/collections_new_metadata/grdi-imr-raster\n", + "writing file: ingestion_data/collections_new_metadata/grdi-shdi-raster\n", + "writing file: ingestion_data/collections_new_metadata/grdi-v1-built\n", + "writing file: ingestion_data/collections_new_metadata/grdi-v1-raster\n", + "writing file: ingestion_data/collections_new_metadata/grdi-vnl-raster\n", + "writing file: ingestion_data/collections_new_metadata/grdi-vnl-slope-raster\n", + "writing file: ingestion_data/collections_new_metadata/CMIP245-winter-median-ta\n", + "writing file: ingestion_data/collections_new_metadata/CMIP585-winter-median-ta\n", + "writing file: ingestion_data/collections_new_metadata/facebook_population_density\n", + "writing file: ingestion_data/collections_new_metadata/sport-lis-vsm0_100cm-percentile\n", + "writing file: ingestion_data/collections_new_metadata/lis-tvegsuppression\n", + "writing file: ingestion_data/collections_new_metadata/mtbs-burn-severity\n", + "writing file: ingestion_data/collections_new_metadata/campfire-albedo-wsa-diff\n", + "writing file: ingestion_data/collections_new_metadata/caldor-fire-behavior\n", + "writing file: ingestion_data/collections_new_metadata/caldor-fire-burn-severity\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Processing\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Production\n", + "writing file: ingestion_data/collections_new_metadata/EPA-monthly-emissions_1B2b_Natural_Gas_Production\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Transmission\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Distribution\n", + "writing file: ingestion_data/collections_new_metadata/lis-tws-anomaly\n", + "writing file: ingestion_data/collections_new_metadata/hls-ndvi\n", + "writing file: ingestion_data/collections_new_metadata/hls-ndvi-difference\n", + "writing file: ingestion_data/collections_new_metadata/houston-aod\n", + "writing file: ingestion_data/collections_new_metadata/snow-projections-diff-245\n", + "writing file: ingestion_data/collections_new_metadata/snow-projections-diff-585\n", + "writing file: ingestion_data/collections_new_metadata/lis-global-da-tws-trend\n", + "writing file: ingestion_data/collections_new_metadata/lis-global-da-gpp-trend\n", + "writing file: ingestion_data/collections_new_metadata/campfire-nlcd\n", + "writing file: ingestion_data/collections_new_metadata/nceo_africa_2017\n", + "writing file: ingestion_data/collections_new_metadata/bangladesh-landcover-2001-2020\n", + "writing file: ingestion_data/collections_new_metadata/social-vulnerability-index-overall\n", + "writing file: ingestion_data/collections_new_metadata/social-vulnerability-index-overall-nopop\n", + "writing file: ingestion_data/collections_new_metadata/nightlights-hd-monthly\n", + "writing file: ingestion_data/collections_new_metadata/hls-entropy-difference\n", + "writing file: ingestion_data/collections_new_metadata/lis-tws-trend\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_6B_Wastewater_Treatment_Domestic\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_6B_Wastewater_Treatment_Industrial\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_6A_Landfills_Industrial\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_6A_Landfills_Municipal\n", + "writing file: ingestion_data/collections_new_metadata/EPA-annual-emissions_6D_Composting\n", + "writing file: ingestion_data/collections_new_metadata/lis-tws-nonstationarity-index\n" + ] + } + ], + "source": [ + "for dataset in dataset_paths:\n", + " with open(dataset) as f:\n", + " post = frontmatter.load(f)\n", + " try:\n", + " infoDesc = re.split(\"::markdown\",post[\"infoDescription\"])[1].replace('\\n', '').strip()\n", + " except:\n", + " pass\n", + " # print(infoDesc) \n", + " layers = post[\"layers\"]\n", + " \n", + " for layer in layers:\n", + " id = layer[\"stacCol\"]\n", + " try:\n", + " info= layer[\"info\"]\n", + " except:\n", + " info=None\n", + " description = layer[\"description\"] + \" \\n\\n ### Technical Details \\n\\n \" + infoDesc \n", + " if id in collection_ids:\n", + " \n", + " with open(f'ingestion-data//production/collections/{id}.json', 'r') as f_collection:\n", + " collection_data = json.load(f_collection)\n", + " collection_data[\"description\"] = description\n", + " if info:\n", + " collection_data[\"providers\"].append({\n", + " \"name\": info[\"source\"],\n", + " \"url\": None,\n", + " \"roles\": [\n", + " \"producer\"\n", + " ]\n", + " })\n", + " with open(f'ingestion-data/production/collections_new_metadata/{id}.json', 'w', encoding='utf-8') as file:\n", + " print(f'writing file: ingestion_data/collections_new_metadata/{id}')\n", + " json.dump(collection_data, file, ensure_ascii=False, indent=4)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c8d394c5-2776-45b4-aea5-e23ed3e9167c", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "6261dbc9-fc39-462e-af22-4f7b3a62bf66", + "metadata": {}, + "outputs": [], + "source": [ + "dev_endpoint = \"https://staging.openveda.cloud\"\n", + "dev_client_id = \"4rhmpnmnk3rgd9qtiuarllppau\"\n", + "dev_user_pool_id = \"us-west-2_0G3VRilt1\"\n", + "dev_identity_pool_id = \"us-west-2:ad6647b6-b410-4e73-8205-28a066c290fb\"\n", + "\n", + "STAC_INGESTOR_API = f\"{dev_endpoint}/api/ingest/\"" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "01b047e4-153a-4b2a-bc19-70fe94de8416", + "metadata": {}, + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "Enter your Cognito username: saadiq\n", + "Enter your Cognito password: ········\n", + "A new password is required. Please provide a new password: ········\n" + ] + } + ], + "source": [ + "client = CognitoClient(\n", + " client_id=dev_client_id,\n", + " user_pool_id=dev_user_pool_id,\n", + " identity_pool_id=dev_identity_pool_id\n", + ")\n", + "_ = client.login()" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "8df24817-5fc6-4378-87cd-1c0d8ac82460", + "metadata": {}, + "outputs": [], + "source": [ + "TOKEN = client.access_token\n", + "\n", + "authorization_header = f\"Bearer {TOKEN}\"\n", + "headers = {\n", + " \"Authorization\": authorization_header,\n", + " \"content-type\": \"application/json\",\n", + " \"accept\": \"application/json\",\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "1a3cd10e-9af1-48d5-8a4f-311c529e2992", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "posting: campfire-lst-night-diff\n" + ] + } + ], + "source": [ + "collection_new_paths = glob.glob('ingestion-data//production/collections_new_metadata/*.json')\n", + "\n", + "ingest_url = f\"{STAC_INGESTOR_API}collections\"\n", + "\n", + "for collection_path in collection_new_paths[:1]:\n", + " with open(collection_path, 'r') as f_collection:\n", + " collection_data = json.load(f_collection)\n", + " collection_id = collection_data[\"id\"]\n", + " print(f\"posting: {collection_id}\")\n", + "\n", + " response = requests.post(ingest_url, json=collection_data, headers=headers)\n", + " response.raise_for_status()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3df7da4d-9630-48ef-84fd-d5fd6da346f3", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b7a54d81-53aa-42a3-93ee-b1f4977225e4", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f5af8214-9f59-43df-a81b-28608b0983dc", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9cf1d2d4-9fd3-4ce4-9e80-9998c273be81", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "15f8543b-a0de-4167-ae30-4b06876749fa", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "91f58028-bced-43bf-9506-4497c07e562e", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.8" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/ingestion-data/production/collections/eis_fire_perimeter.json b/ingestion-data/production/collections/eis_fire_perimeter.json index 0c2be99..16db67b 100644 --- a/ingestion-data/production/collections/eis_fire_perimeter.json +++ b/ingestion-data/production/collections/eis_fire_perimeter.json @@ -51,8 +51,8 @@ "stac_version": "1.0.0", "providers": [ { - "name": "NASA National Oceanic and Atmospheric Administration", - "url": "https://www.nasa.gov/directorates/smd/joint-agency-satellite-division/noaa/", + "name": "NOAA", + "url": "https://www.noaa.gov", "roles": [ "producer" ] diff --git a/ingestion-data/production/collections_new_metadata/CMIP245-winter-median-pr.json b/ingestion-data/production/collections_new_metadata/CMIP245-winter-median-pr.json new file mode 100644 index 0000000..f90e2a2 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/CMIP245-winter-median-pr.json @@ -0,0 +1,95 @@ +{ + "id": "CMIP245-winter-median-pr", + "type": "Collection", + "title": "Projected changes to winter (January, February, and March) cumulative daily precipitation", + "links": [], + "description": "Percent difference in projected winter (January, February, March) cumulative precipitation, relative to a historical timeframe between 1995 and 2014. Outputs represent the median of 23 member ensembles from CMIP6 (SSP 2-4.5) with downscaling performed by NASA Earth Exchange \n\n ### Technical Details \n\n Future changes to precipitation are expected to alter the volume and timing of snow water resources. Here, we present the projected percent-change to Western US cumulative winter precipitation at quarter-degree spatial resoutions across 20-year time periods between 2016 and 2095. Projections are averaged from an ensemble of 23 downscaled climate models from the CMIP6 NASA Earth Exchange Global Daily Downscaled Projections.", + "extent": { + "spatial": { + "bbox": [ + [ + -126, + 30, + -104, + 51 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2025-01-01T00:00:00Z", + "2085-03-31T12:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "nodata": "nan", + "colormap_name": "rdbu", + "rescale": [ + [ + -60, + 60 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Center for Climate Simulation (NCCS)", + "url": "https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-gddp-cmip6", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by Justin Pflug (Photo of Nisqually glacier)", + "href": "https://thumbnails.openveda.cloud/CMIP-winter-median.jpeg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/CMIP245-winter-median-ta.json b/ingestion-data/production/collections_new_metadata/CMIP245-winter-median-ta.json new file mode 100644 index 0000000..ac9c852 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/CMIP245-winter-median-ta.json @@ -0,0 +1,94 @@ +{ + "id": "CMIP245-winter-median-ta", + "type": "Collection", + "title": "Projected changes to winter (January, February, and March) average daily air temperature", + "links": [], + "description": "Difference in projected winter (January, February, March) average air temperature, relative to a historical timeframe between 1995 and 2014. Outputs represent the median of 23 member ensembles from CMIP6 (SSP 2-4.5) with downscaling performed by NASA Earth Exchange \n\n ### Technical Details \n\n Future changes to air temperature are expected to influence the phase of winter precipitation (snowfall or rainfall) and the timing and amount of snowmelt and streamflow. Here, we present the projected percent-change to Western US average winter temperature at quarter-degree spatial resoutions across 20-year time periods between 2016 and 2095. Projections are averaged from an ensemble of 23 downscaled climate models from the [CMIP6 NASA Earth Exchange Global Daily Downscaled Projections](https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-gddp-cmip6).", + "extent": { + "spatial": { + "bbox": [ + [ + -126, + 30, + -104, + 51 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2025-01-01T00:00:00Z", + "2085-03-31T12:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "rdbu_r", + "rescale": [ + [ + -5.5, + 5.5 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Center for Climate Simulation (NCCS)", + "url": "https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-gddp-cmip6", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by Justin Pflug (Photo of Nisqually glacier)", + "href": "https://thumbnails.openveda.cloud/CMIP-winter-median.jpeg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/CMIP585-winter-median-pr.json b/ingestion-data/production/collections_new_metadata/CMIP585-winter-median-pr.json new file mode 100644 index 0000000..40cde00 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/CMIP585-winter-median-pr.json @@ -0,0 +1,95 @@ +{ + "id": "CMIP585-winter-median-pr", + "type": "Collection", + "title": "Projected changes to winter (January, February, and March) cumulative daily precipitation", + "links": [], + "description": "Percent difference in projected winter (January, February, March) cumulative precipitation, relative to a historical timeframe between 1995 and 2014. Outputs represent the median of 23 member ensembles from CMIP6 (SSP 5-8.5) with downscaling performed by NASA Earth Exchange \n\n ### Technical Details \n\n Future changes to precipitation are expected to alter the volume and timing of snow water resources. Here, we present the projected percent-change to Western US cumulative winter precipitation at quarter-degree spatial resoutions across 20-year time periods between 2016 and 2095. Projections are averaged from an ensemble of 23 downscaled climate models from the CMIP6 NASA Earth Exchange Global Daily Downscaled Projections.", + "extent": { + "spatial": { + "bbox": [ + [ + -126, + 30, + -104, + 51 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2025-01-01T00:00:00Z", + "2085-03-31T12:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "nodata": "nan", + "colormap_name": "rdbu", + "rescale": [ + [ + -60, + 60 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Center for Climate Simulation (NCCS)", + "url": "https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-gddp-cmip6", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by Justin Pflug (Photo of Nisqually glacier)", + "href": "https://thumbnails.openveda.cloud/CMIP-winter-median.jpeg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/CMIP585-winter-median-ta.json b/ingestion-data/production/collections_new_metadata/CMIP585-winter-median-ta.json new file mode 100644 index 0000000..695aacf --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/CMIP585-winter-median-ta.json @@ -0,0 +1,94 @@ +{ + "id": "CMIP585-winter-median-ta", + "type": "Collection", + "title": "Projected changes to winter (January, February, and March) average daily air temperature", + "links": [], + "description": "Difference in projected winter (January, February, March) average air temperature, relative to a historical timeframe between 1995 and 2014. Outputs represent the median of 23 member ensembles from CMIP6 (SSP 5-8.5) with downscaling performed by NASA Earth Exchange \n\n ### Technical Details \n\n Future changes to air temperature are expected to influence the phase of winter precipitation (snowfall or rainfall) and the timing and amount of snowmelt and streamflow. Here, we present the projected percent-change to Western US average winter temperature at quarter-degree spatial resoutions across 20-year time periods between 2016 and 2095. Projections are averaged from an ensemble of 23 downscaled climate models from the [CMIP6 NASA Earth Exchange Global Daily Downscaled Projections](https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-gddp-cmip6).", + "extent": { + "spatial": { + "bbox": [ + [ + -126, + 30, + -104, + 51 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2025-01-01T00:00:00Z", + "2085-03-31T12:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "rdbu_r", + "rescale": [ + [ + -5.5, + 5.5 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Center for Climate Simulation (NCCS)", + "url": "https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-gddp-cmip6", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by Justin Pflug (Photo of Nisqually glacier)", + "href": "https://thumbnails.openveda.cloud/CMIP-winter-median.jpeg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1A_Combustion_Mobile.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1A_Combustion_Mobile.json new file mode 100644 index 0000000..d2864c7 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1A_Combustion_Mobile.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_1A_Combustion_Mobile", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Mobile Combustion", + "links": [], + "description": "Mobile emissions from sector 1A, including on-road and non-road vehicles, waterborne, rail, and air. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 1126809681 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Harry Schaefer / Documerica](https://unsplash.com/photos/EjSw6WdnLRA) (Orange Ford truck leaving a Union Carbide ferro-alloy plant. Shot on May 1975)", + "href": "https://thumbnails.openveda.cloud/epa-other--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1A_Combustion_Stationary.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1A_Combustion_Stationary.json new file mode 100644 index 0000000..a38e59e --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1A_Combustion_Stationary.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_1A_Combustion_Stationary", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Stationary Combustion", + "links": [], + "description": "Stationary (non-mobile) emissions from sector 1A, including boilers, heaters, furnaces, kilns, ovens, flares, thermal oxidizers, dryers, and any other equipment or machinery that combusts carbon bearing fuels or waste stream materials. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 11699984793 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Harry Schaefer / Documerica](https://unsplash.com/photos/EjSw6WdnLRA) (Orange Ford truck leaving a Union Carbide ferro-alloy plant. Shot on May 1975)", + "href": "https://thumbnails.openveda.cloud/epa-other--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B1a_Abandoned_Coal.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B1a_Abandoned_Coal.json new file mode 100644 index 0000000..ef3f598 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B1a_Abandoned_Coal.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_1B1a_Abandoned_Coal", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Abandoned Coal Mines", + "links": [], + "description": "Emissions from sector 1B1a from abandoned coal mines. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 90163894026 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Dominik Vanyi](https://unsplash.com/photos/Mk2ls9UBO2E) (Machinery working a very large coal mine)", + "href": "https://thumbnails.openveda.cloud/epa-coal-mines--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B1a_Coal_Mining_Surface.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B1a_Coal_Mining_Surface.json new file mode 100644 index 0000000..2e9b42b --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B1a_Coal_Mining_Surface.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_1B1a_Coal_Mining_Surface", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Surface Coal Mines", + "links": [], + "description": "Emissions from sector 1B1a from surface coal mining. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 1002466086748 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Dominik Vanyi](https://unsplash.com/photos/Mk2ls9UBO2E) (Machinery working a very large coal mine)", + "href": "https://thumbnails.openveda.cloud/epa-coal-mines--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B1a_Coal_Mining_Underground.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B1a_Coal_Mining_Underground.json new file mode 100644 index 0000000..e575e1a --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B1a_Coal_Mining_Underground.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_1B1a_Coal_Mining_Underground", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Underground Coal Mines", + "links": [], + "description": "Emissions from sector 1B1a from underground coal mining. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 2022634652958 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Dominik Vanyi](https://unsplash.com/photos/Mk2ls9UBO2E) (Machinery working a very large coal mine)", + "href": "https://thumbnails.openveda.cloud/epa-coal-mines--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2a_Petroleum.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2a_Petroleum.json new file mode 100644 index 0000000..f89e495 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2a_Petroleum.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_1B2a_Petroleum", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Petroleum", + "links": [], + "description": "Non-combustion emissions from sector 1B2a for petroleum systems, including production, transportation, and refining. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 282207914557 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Patrick Hendry](https://unsplash.com/photos/6xeDIZgoPaw) (Punk style picture of a petroleum refinery)", + "href": "https://thumbnails.openveda.cloud/epa-petroleum--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Distribution.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Distribution.json new file mode 100644 index 0000000..fc6a23f --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Distribution.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_1B2b_Natural_Gas_Distribution", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Natural Gas Distribution", + "links": [], + "description": "Non-combustion emissions from sector 1B2b for natural gas distribution. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 32621776076 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [American Public Power Association](https://unsplash.com/photos/TF-DL_2L1JM) (Gas processing plant at dusk)", + "href": "https://thumbnails.openveda.cloud/epa-natural-gas--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Processing.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Processing.json new file mode 100644 index 0000000..57e89db --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Processing.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_1B2b_Natural_Gas_Processing", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Natural Gas Processing", + "links": [], + "description": "Non-combustion emissions from sector 1B2b for natural gas processing. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 963867416985 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [American Public Power Association](https://unsplash.com/photos/TF-DL_2L1JM) (Gas processing plant at dusk)", + "href": "https://thumbnails.openveda.cloud/epa-natural-gas--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Production.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Production.json new file mode 100644 index 0000000..59ea712 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Production.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_1B2b_Natural_Gas_Production", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Natural Gas Production", + "links": [], + "description": "Non-combustion emissions from sector 1B2b for natural gas production. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 194600207646 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [American Public Power Association](https://unsplash.com/photos/TF-DL_2L1JM) (Gas processing plant at dusk)", + "href": "https://thumbnails.openveda.cloud/epa-natural-gas--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Transmission.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Transmission.json new file mode 100644 index 0000000..1b8c1db --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_1B2b_Natural_Gas_Transmission.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_1B2b_Natural_Gas_Transmission", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Natural Gas Transmission", + "links": [], + "description": "Non-combustion emissions from sector 1B2b for natural gas transmission. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 138826376806 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [American Public Power Association](https://unsplash.com/photos/TF-DL_2L1JM) (Gas processing plant at dusk)", + "href": "https://thumbnails.openveda.cloud/epa-natural-gas--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_2B5_Petrochemical_Production.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_2B5_Petrochemical_Production.json new file mode 100644 index 0000000..bbcc44f --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_2B5_Petrochemical_Production.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_2B5_Petrochemical_Production", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Petrochemical Production", + "links": [], + "description": "Emissions from sector 2B5 from petrochemical production. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 3715968204 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Harry Schaefer / Documerica](https://unsplash.com/photos/EjSw6WdnLRA) (Orange Ford truck leaving a Union Carbide ferro-alloy plant. Shot on May 1975)", + "href": "https://thumbnails.openveda.cloud/epa-other--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_2C2_Ferroalloy_Production.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_2C2_Ferroalloy_Production.json new file mode 100644 index 0000000..bf18cbe --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_2C2_Ferroalloy_Production.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_2C2_Ferroalloy_Production", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Ferroalloy Production", + "links": [], + "description": "Emissions from sector 2C2 from ferroalloy production. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 2316570132 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Harry Schaefer / Documerica](https://unsplash.com/photos/EjSw6WdnLRA) (Orange Ford truck leaving a Union Carbide ferro-alloy plant. Shot on May 1975)", + "href": "https://thumbnails.openveda.cloud/epa-other--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_4A_Enteric_Fermentation.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_4A_Enteric_Fermentation.json new file mode 100644 index 0000000..c245e34 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_4A_Enteric_Fermentation.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_4A_Enteric_Fermentation", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Enteric Fermentation", + "links": [], + "description": "Emissions from sector 4A from enteric fermentation (fermentation that takes place in the digestive systems of animals). \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 43784598420 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [James Baltz](https://unsplash.com/photos/jAt6cN6zl8M) (Tractors tending a corn field)", + "href": "https://thumbnails.openveda.cloud/epa-agriculture--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_4B_Manure_Management.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_4B_Manure_Management.json new file mode 100644 index 0000000..f67148a --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_4B_Manure_Management.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_4B_Manure_Management", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Manure Management", + "links": [], + "description": "Emissions from sector 4B from manure management. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 46428019752 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [James Baltz](https://unsplash.com/photos/jAt6cN6zl8M) (Tractors tending a corn field)", + "href": "https://thumbnails.openveda.cloud/epa-agriculture--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_4C_Rice_Cultivation.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_4C_Rice_Cultivation.json new file mode 100644 index 0000000..6b41b1c --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_4C_Rice_Cultivation.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_4C_Rice_Cultivation", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Rice Cultivation", + "links": [], + "description": "Emissions from sector 4C from rice cultivation. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 38327875010 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [James Baltz](https://unsplash.com/photos/jAt6cN6zl8M) (Tractors tending a corn field)", + "href": "https://thumbnails.openveda.cloud/epa-agriculture--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_4F_Field_Burning.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_4F_Field_Burning.json new file mode 100644 index 0000000..6245d54 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_4F_Field_Burning.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_4F_Field_Burning", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Field Burning", + "links": [], + "description": "Emissions from sector 4F from agricultural field burning. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 800788398 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [James Baltz](https://unsplash.com/photos/jAt6cN6zl8M) (Tractors tending a corn field)", + "href": "https://thumbnails.openveda.cloud/epa-agriculture--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_5_Forest_Fires.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_5_Forest_Fires.json new file mode 100644 index 0000000..af7f7cb --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_5_Forest_Fires.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_5_Forest_Fires", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Forest Fires", + "links": [], + "description": "Emissions from sector 5 from forest fires. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 23039817809 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Harry Schaefer / Documerica](https://unsplash.com/photos/EjSw6WdnLRA) (Orange Ford truck leaving a Union Carbide ferro-alloy plant. Shot on May 1975)", + "href": "https://thumbnails.openveda.cloud/epa-other--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6A_Landfills_Industrial.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6A_Landfills_Industrial.json new file mode 100644 index 0000000..7d6cfc5 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6A_Landfills_Industrial.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_6A_Landfills_Industrial", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Industrial Landfills", + "links": [], + "description": "Emissions from sector 6A from non-municipal solid waste landfills used to to dispose of industrial solid waste. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 249776633282 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Antoine GIRET](https://unsplash.com/photos/7_TSzqJms4w) (Mountain of rubbish and garbage on the beach by the sea)", + "href": "https://thumbnails.openveda.cloud/epa-waste--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6A_Landfills_Municipal.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6A_Landfills_Municipal.json new file mode 100644 index 0000000..565dc1d --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6A_Landfills_Municipal.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_6A_Landfills_Municipal", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Municipal Landfills", + "links": [], + "description": "Emissions from sector 6A from municipal solid waste landfills receiving household waste. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 675446396026 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Antoine GIRET](https://unsplash.com/photos/7_TSzqJms4w) (Mountain of rubbish and garbage on the beach by the sea)", + "href": "https://thumbnails.openveda.cloud/epa-waste--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6B_Wastewater_Treatment_Domestic.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6B_Wastewater_Treatment_Domestic.json new file mode 100644 index 0000000..2348f84 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6B_Wastewater_Treatment_Domestic.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_6B_Wastewater_Treatment_Domestic", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Domestic Wastewater Treatment", + "links": [], + "description": "Emissions from sector 6B from wastewater treatment of domestic sewage. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 91901814374 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Antoine GIRET](https://unsplash.com/photos/7_TSzqJms4w) (Mountain of rubbish and garbage on the beach by the sea)", + "href": "https://thumbnails.openveda.cloud/epa-waste--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6B_Wastewater_Treatment_Industrial.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6B_Wastewater_Treatment_Industrial.json new file mode 100644 index 0000000..2a83af1 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6B_Wastewater_Treatment_Industrial.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_6B_Wastewater_Treatment_Industrial", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Industrial Wastewater Treatment", + "links": [], + "description": "Emissions from sector 6B from wastewater treatment of industrial and commercial sources. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 1283751631912 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Antoine GIRET](https://unsplash.com/photos/7_TSzqJms4w) (Mountain of rubbish and garbage on the beach by the sea)", + "href": "https://thumbnails.openveda.cloud/epa-waste--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6D_Composting.json b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6D_Composting.json new file mode 100644 index 0000000..d192adc --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-annual-emissions_6D_Composting.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-annual-emissions_6D_Composting", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Composting", + "links": [], + "description": "Emissions from sector 6D from composting. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 7718224527 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Antoine GIRET](https://unsplash.com/photos/7_TSzqJms4w) (Mountain of rubbish and garbage on the beach by the sea)", + "href": "https://thumbnails.openveda.cloud/epa-waste--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-daily-emissions_5_Forest_Fires.json b/ingestion-data/production/collections_new_metadata/EPA-daily-emissions_5_Forest_Fires.json new file mode 100644 index 0000000..170d076 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-daily-emissions_5_Forest_Fires.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-daily-emissions_5_Forest_Fires", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Forest Fires (daily)", + "links": [], + "description": "Emissions from sector 5 from forest fires (daily). \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 1690773099642 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Harry Schaefer / Documerica](https://unsplash.com/photos/EjSw6WdnLRA) (Orange Ford truck leaving a Union Carbide ferro-alloy plant. Shot on May 1975)", + "href": "https://thumbnails.openveda.cloud/epa-other--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_1A_Combustion_Stationary.json b/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_1A_Combustion_Stationary.json new file mode 100644 index 0000000..b2175eb --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_1A_Combustion_Stationary.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-monthly-emissions_1A_Combustion_Stationary", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Stationary Combustion (monthly)", + "links": [], + "description": "Stationary (non-mobile) emissions from sector 1A, including boilers, heaters, furnaces, kilns, ovens, flares, thermal oxidizers, dryers, and any other equipment or machinery that combusts carbon bearing fuels or waste stream materials. \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 11792563568 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Harry Schaefer / Documerica](https://unsplash.com/photos/EjSw6WdnLRA) (Orange Ford truck leaving a Union Carbide ferro-alloy plant. Shot on May 1975)", + "href": "https://thumbnails.openveda.cloud/epa-other--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_1B2a_Petroleum.json b/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_1B2a_Petroleum.json new file mode 100644 index 0000000..5859b22 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_1B2a_Petroleum.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-monthly-emissions_1B2a_Petroleum", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Petroleum (monthly)", + "links": [], + "description": "Non-combustion emissions from sector 1B2a for petroleum systems, including production, transportation, and refining (monthly). \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 376365761167 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Patrick Hendry](https://unsplash.com/photos/6xeDIZgoPaw) (Punk style picture of a petroleum refinery)", + "href": "https://thumbnails.openveda.cloud/epa-petroleum--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_1B2b_Natural_Gas_Production.json b/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_1B2b_Natural_Gas_Production.json new file mode 100644 index 0000000..20b976a --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_1B2b_Natural_Gas_Production.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-monthly-emissions_1B2b_Natural_Gas_Production", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Natural Gas Production (monthly)", + "links": [], + "description": "Non-combustion emissions from sector 1B2b for natural gas production (monthly). \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 201580808765 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [American Public Power Association](https://unsplash.com/photos/TF-DL_2L1JM) (Gas processing plant at dusk)", + "href": "https://thumbnails.openveda.cloud/epa-natural-gas--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_4B_Manure_Management.json b/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_4B_Manure_Management.json new file mode 100644 index 0000000..35c233e --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_4B_Manure_Management.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-monthly-emissions_4B_Manure_Management", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Manure Management (monthly)", + "links": [], + "description": "Emissions from sector 4B from manure management (monthly). \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 46428019752 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [James Baltz](https://unsplash.com/photos/jAt6cN6zl8M) (Tractors tending a corn field)", + "href": "https://thumbnails.openveda.cloud/epa-agriculture--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_4C_Rice_Cultivation.json b/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_4C_Rice_Cultivation.json new file mode 100644 index 0000000..0909b31 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_4C_Rice_Cultivation.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-monthly-emissions_4C_Rice_Cultivation", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Rice Cultivation (monthly)", + "links": [], + "description": "Emissions from sector 4C from rice cultivation (monthly). \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 54815427133 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [James Baltz](https://unsplash.com/photos/jAt6cN6zl8M) (Tractors tending a corn field)", + "href": "https://thumbnails.openveda.cloud/epa-agriculture--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_4F_Field_Burning.json b/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_4F_Field_Burning.json new file mode 100644 index 0000000..695eff9 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/EPA-monthly-emissions_4F_Field_Burning.json @@ -0,0 +1,91 @@ +{ + "id": "EPA-monthly-emissions_4F_Field_Burning", + "type": "Collection", + "title": "Gridded 2012 EPA Methane Emissions - Field Burning (monthly)", + "links": [], + "description": "Emissions from sector 4F from agricultural field burning (monthly). \n\n ### Technical Details \n\n A team at Harvard University along with EPA and other coauthors developed a gridded inventory of U.S. anthropogenic methane emissions with 0.1° x 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 U.S. [EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/us-greenhouse-gas-inventory-report-1990-2014) estimates for the year 2012, which presents national totals for different source types. The gridded inventory was developed using a wide range of databases at the state, county, local, and point source level to allocate the spatial and temporal distribution of emissions for individual source types.", + "extent": { + "spatial": { + "bbox": [ + [ + -129.99999694660497, + 19.999999240339655, + -59.999999238697754, + 54.99999694496308 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2012-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rainbow", + "rescale": [ + [ + 0, + 4510689853 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "EPA", + "url": "https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [James Baltz](https://unsplash.com/photos/jAt6cN6zl8M) (Tractors tending a corn field)", + "href": "https://thumbnails.openveda.cloud/epa-agriculture--cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/IS2SITMOGR4-cog.json b/ingestion-data/production/collections_new_metadata/IS2SITMOGR4-cog.json new file mode 100644 index 0000000..4200bb4 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/IS2SITMOGR4-cog.json @@ -0,0 +1,90 @@ +{ + "id": "IS2SITMOGR4-cog", + "type": "Collection", + "title": "ICESat-2 L4 Monthly Gridded Sea Ice Thickness (COGs)", + "links": [], + "description": "Sea Ice thickness in meters \n\n ### Technical Details \n\n This data set reports monthly, gridded winter sea ice thickness across the Arctic Ocean. Sea ice thickness is estimated using ATLAS/ICESat-2 L3A Sea Ice Freeboard (ATL10), Version 5 data and NASA Eulerian Snow On Sea Ice Model (NESOSIM) snow loading.", + "extent": { + "spatial": { + "bbox": [ + [ + -180, + 31.269270721494188, + 179.7061752664782, + 85.18898561151076 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2018-11-01T00:00:00Z", + "2021-04-30T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "plasma", + "rescale": [ + [ + 0, + 16 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "National Snow And Ice Data Center (NSIDC)", + "url": "https://nsidc.org/data/explore-data", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Matt Broch](https://unsplash.com/photos/bwD3GLrV4pY) (Huge chunk of ice calving into the sea below)", + "href": "https://thumbnails.openveda.cloud/sea-ice-thick--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/MO_NPP_npp_vgpm.json b/ingestion-data/production/collections_new_metadata/MO_NPP_npp_vgpm.json new file mode 100644 index 0000000..32bf0a6 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/MO_NPP_npp_vgpm.json @@ -0,0 +1,88 @@ +{ + "id": "MO_NPP_npp_vgpm", + "type": "Collection", + "title": "", + "links": [], + "description": "Ocean Net Primary Production (NPP) \n\n ### Technical Details \n\n Find information at the [Ocean Productivity website](https://sites.science.oregonstate.edu/ocean.productivity/index.php)", + "extent": { + "spatial": { + "bbox": [ + [ + -180.0000050868518, + -90.00000508655744, + 180.0000050868518, + 89.9999974571629 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2020-01-01T00:00:00Z", + "2020-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "jet", + "rescale": [ + [ + 0, + 1500 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "Oregon State University", + "url": "https://sites.science.oregonstate.edu/ocean.productivity", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Karl Callwood](https://unsplash.com/photos/Ko1sGLhZm5w) (Rocky ocean shore)", + "href": "https://thumbnails.openveda.cloud/ocean-production--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/OMI_trno2-COG.json b/ingestion-data/production/collections_new_metadata/OMI_trno2-COG.json new file mode 100644 index 0000000..a66524e --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/OMI_trno2-COG.json @@ -0,0 +1,88 @@ +{ + "id": "OMI_trno2-COG", + "type": "Collection", + "title": "OMI_trno2 - 0.10 x 0.10 Annual as Cloud-Optimized GeoTIFFs (COGs)", + "links": [], + "description": "NASA OMI/Aura Nitrogen Dioxide (NO₂) Total and Tropospheric Column \n\n ### Technical Details \n\n OMI, which launched in 2004, preceded TROPOMI, which launched in 2017. While TROPOMI provides higher resolution information, the longer OMI data record provides context for the TROPOMI observations.", + "extent": { + "spatial": { + "bbox": [ + [ + -180, + -90, + 180, + 90 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2005-01-01T00:00:00Z", + "2022-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "reds", + "rescale": [ + [ + 0, + 3000000000000000.0 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA", + "url": "https://aura.gsfc.nasa.gov/omi.html", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mick Truyts](https://unsplash.com/photos/x6WQeNYJC1w) (Power plant shooting steam at the sky)", + "href": "https://thumbnails.openveda.cloud/no2--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/OMSO2PCA-COG.json b/ingestion-data/production/collections_new_metadata/OMSO2PCA-COG.json new file mode 100644 index 0000000..74a01c3 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/OMSO2PCA-COG.json @@ -0,0 +1,92 @@ +{ + "id": "OMSO2PCA-COG", + "type": "Collection", + "title": "OMI/Aura Sulfur Dioxide (SO2) Total Column L3 1 day Best Pixel in 0.25 degree x 0.25 degree V3 as Cloud-Optimized GeoTIFFs (COGs)", + "links": [], + "description": "NASA OMI/Aura Sulfur Dioxide (SO2) Total Column \n\n ### Technical Details \n\n The OMI Sulfur Dioxide (SO2) Total Column layer indicates the column density of sulfur dioxide and is measured in Dobson Units (DU). Sulfur Dioxide and Aerosol Index products are used to monitor volcanic clouds and detect pre-eruptive volcanic degassing globally. This information is used by the Volcanic Ash Advisory Centers in advisories to airlines for operational decision", + "extent": { + "spatial": { + "bbox": [ + [ + -180, + -90, + 180, + 90 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2005-01-01T00:00:00Z", + "2021-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "rdylbu_r", + "rescale": [ + [ + 0, + 1 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA", + "url": "https://aura.gsfc.nasa.gov/omi.html", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA (2018 Social Vulnerability Index (SVI) based on minority status and language score)", + "href": "https://thumbnails.openveda.cloud/so2--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/bangladesh-landcover-2001-2020.json b/ingestion-data/production/collections_new_metadata/bangladesh-landcover-2001-2020.json new file mode 100644 index 0000000..60169ab --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/bangladesh-landcover-2001-2020.json @@ -0,0 +1,132 @@ +{ + "id": "bangladesh-landcover-2001-2020", + "type": "Collection", + "title": "Annual land cover maps for 2001 and 2020", + "links": [], + "description": "Annual land cover maps for 2001 and 2020 (Bangladesh) \n\n ### Technical Details \n\n The annual land cover maps of 2001 and 2021 were captured using combined Moderate Resolution Imaging Spectroradiometer (MODIS) Annual Land Cover Type dataset (MCD12Q1 V6, dataset link: [https://lpdaac.usgs.gov/products/mcd12q1v006/](https://lpdaac.usgs.gov/products/mcd12q1v006/)). The actual data product provides global land cover types at yearly intervals (2001-2020) at 500 meters with six different types of land cover classification. Among six different schemes, The International Geosphere–Biosphere Programme (IGBP) land cover classification selected and further simplified to dominant land cover classes (water, urban, cropland, native vegetation) for two different years to illustrate the changes in land use and land cover of the country.", + "extent": { + "spatial": { + "bbox": [ + [ + 88.02591469087191, + 20.742099910319755, + 92.68367943903164, + 26.63504817414382 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2001-01-01T00:00:00Z", + "2020-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:datetime_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "nearest", + "colormap": { + "0": [ + 0, + 0, + 0, + 128 + ], + "100": [ + 0, + 130, + 0, + 255 + ], + "200": [ + 17, + 131, + 226, + 255 + ], + "300": [ + 199, + 43, + 32, + 255 + ], + "400": [ + 98, + 234, + 37, + 255 + ] + }, + "bidx": [ + 1 + ], + "return_mask": true, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [USGS](https://unsplash.com/photos/d59NHNtT_Ss) (Annual land cover maps for 2001 and 2020 (Bangladesh))", + "href": "https://thumbnails.openveda.cloud/bangladesh-landcover-2001-2020--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/barc-thomasfire.json b/ingestion-data/production/collections_new_metadata/barc-thomasfire.json new file mode 100644 index 0000000..2dfd955 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/barc-thomasfire.json @@ -0,0 +1,96 @@ +{ + "id": "barc-thomasfire", + "type": "Collection", + "title": "Burn Area Reflectance Classification for Thomas Fire", + "links": [], + "description": "Burn Area Reflectance Classification (BARC) from the Burned Area Emergency Response (BAER) program for the Thomas Fire of 2017 \n\n ### Technical Details \n\n Maximum Fire Radiative Power recorded by the Suomi NPP VIIRS sensor per 12hr fire line segment for the Thomas Fire of 2017", + "extent": { + "spatial": { + "bbox": [ + [ + -119.7279834250452, + 34.19572604525683, + -118.88724142537933, + 34.72668711929945 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-12-01T00:00:00Z", + "2017-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rdylgn_r", + "rescale": [ + [ + 1, + 4 + ] + ], + "nodata": "nan", + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS Burnt Area Emergency Response (BAER)", + "url": "https://burnseverity.cr.usgs.gov/products/baer", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mike Newbry](https://unsplash.com/photos/DwtX9mMHBJ0) (Hillside engulfed by wildfire)", + "href": "https://thumbnails.openveda.cloud/mtbs-burn-severity--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/blue-tarp-detection.json b/ingestion-data/production/collections_new_metadata/blue-tarp-detection.json new file mode 100644 index 0000000..b72d899 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/blue-tarp-detection.json @@ -0,0 +1,92 @@ +{ + "id": "blue-tarp-detection", + "type": "Collection", + "title": "Hurricane Ida - Detected Blue Tarps", + "links": [], + "description": "machine learning generated blue tarp detections. Includes copyrighted material of Planet. All rights reserved. \n\n ### Technical Details \n\n Planetscope provides 3-band RGB imagery at 3-meter ground resolution which can support building-scale analysis of the land surface. In the aftermath of natural disasters associated with high wind speeds, homes with damaged roofs typically are covered with blue tarps to protect the interior of the home from further damage. Using machine learning, blue tarps can be detected from the Planetscope imagery using pre-event cloud free images to detect blue pixels and potential impacts after a natural disaster.", + "extent": { + "spatial": { + "bbox": [ + [ + -90.27360106927819, + 18.30419449685249, + -65.97626446723649, + 30.05152357730603 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-02-11T00:00:00Z", + "2022-02-12T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default blue-tarp detection layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "cubic_spline", + "bidx": [ + 1 + ], + "colormap_name": "reds", + "rescale": [ + [ + 0, + 400 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA IMPACT", + "url": "https://impact.earthdata.nasa.gov/", + "roles": [ + "producer" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA (Blue tarp detections for Jefferson Parish, LA on February 12, 2022)", + "href": "https://thumbnails.openveda.cloud/ps-bluetarp--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/blue-tarp-planetscope.json b/ingestion-data/production/collections_new_metadata/blue-tarp-planetscope.json new file mode 100644 index 0000000..8b647fe --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/blue-tarp-planetscope.json @@ -0,0 +1,72 @@ +{ + "id": "blue-tarp-planetscope", + "type": "Collection", + "title": "Hurricane Ida - Blue Tarps PlanetScope Image", + "links": [], + "description": "Planetscope input RGB imagery used for blue tarp detection. Includes copyrighted material of Planet. All rights reserved. \n\n ### Technical Details \n\n Planetscope provides 3-band RGB imagery at 3-meter ground resolution which can support building-scale analysis of the land surface. In the aftermath of natural disasters associated with high wind speeds, homes with damaged roofs typically are covered with blue tarps to protect the interior of the home from further damage. Using machine learning, blue tarps can be detected from the Planetscope imagery using pre-event cloud free images to detect blue pixels and potential impacts after a natural disaster.", + "extent": { + "spatial": { + "bbox": [ + [ + -90.27360950831685, + 18.30419449685249, + -65.97626446723649, + 30.051540153516584 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-02-11T00:00:00Z", + "2022-02-12T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default base PlanetScope image (used for blue-tarp detection) layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "providers": [ + { + "name": "NASA IMPACT", + "url": "https://impact.earthdata.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA (Blue tarp detections for Jefferson Parish, LA on February 12, 2022)", + "href": "https://thumbnails.openveda.cloud/ps-bluetarp--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/caldor-fire-behavior.json b/ingestion-data/production/collections_new_metadata/caldor-fire-behavior.json new file mode 100644 index 0000000..9573a49 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/caldor-fire-behavior.json @@ -0,0 +1,95 @@ +{ + "id": "caldor-fire-behavior", + "type": "Collection", + "title": "Caldor Fire Behavior", + "links": [], + "description": " \n\n ### Technical Details \n\n This dataset describes the progression and active fire behavior of the 2021 Caldor Fire in California, as recorded by the algorithm detailed in https://www.nature.com/articles/s41597-022-01343-0. It includes an extra layer detailing the soil burn severity (SBS) conditions provided by the [Burned Area Emergency Response](https://burnseverity.cr.usgs.gov/baer/) team.", + "extent": { + "spatial": { + "bbox": [ + [ + -120.61338752166166, + 38.54940283865057, + -119.91905658168675, + 38.90577651328637 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2021-08-15T00:00:00Z", + "2021-10-21T12:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "inferno_r", + "rescale": [ + [ + 0, + 93 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS Burnt Area Emergency Response (BAER)", + "url": "https://burnseverity.cr.usgs.gov/products/baer", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Marek Piwnicki](https://unsplash.com/photos/WiZOyYqzUss) (Hillside engulfed by a wildfire)", + "href": "https://thumbnails.openveda.cloud/caldor-fire--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/caldor-fire-burn-severity.json b/ingestion-data/production/collections_new_metadata/caldor-fire-burn-severity.json new file mode 100644 index 0000000..5c521ca --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/caldor-fire-burn-severity.json @@ -0,0 +1,95 @@ +{ + "id": "caldor-fire-burn-severity", + "type": "Collection", + "title": "Caldor Fire Burn Severity", + "links": [], + "description": "Soil burn severity (SBS) conditions. \n\n ### Technical Details \n\n This dataset describes the progression and active fire behavior of the 2021 Caldor Fire in California, as recorded by the algorithm detailed in https://www.nature.com/articles/s41597-022-01343-0. It includes an extra layer detailing the soil burn severity (SBS) conditions provided by the [Burned Area Emergency Response](https://burnseverity.cr.usgs.gov/baer/) team.", + "extent": { + "spatial": { + "bbox": [ + [ + -120.61338752166166, + 38.549319926107025, + -119.91919400099995, + 38.90577651328637 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2021-08-15T00:00:00Z", + "2021-10-21T12:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "inferno_r", + "rescale": [ + [ + 0, + 5 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS Burnt Area Emergency Response (BAER)", + "url": "https://burnseverity.cr.usgs.gov/products/baer", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Marek Piwnicki](https://unsplash.com/photos/WiZOyYqzUss) (Hillside engulfed by a wildfire)", + "href": "https://thumbnails.openveda.cloud/caldor-fire--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/campfire-albedo-wsa-diff.json b/ingestion-data/production/collections_new_metadata/campfire-albedo-wsa-diff.json new file mode 100644 index 0000000..23e73ea --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/campfire-albedo-wsa-diff.json @@ -0,0 +1,72 @@ +{ + "id": "campfire-albedo-wsa-diff", + "type": "Collection", + "title": "Camp Fire Domain: MODIS WSA Albedo Difference", + "links": [], + "description": "3-year average difference (2018-2022) - (2015-2018) MODIS-derived Albedo WSA over the 2018 Camp Fire burn scar domain. \n\n ### Technical Details \n\n In order to examine how the fire event affected the changes in surface properties, we utilized the MODIS-derived Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) products for a six-year period centered on the Camp Fire event (2015-2022). We used these products which are available at 16-day intervals to compute monthly averaged spatial maps of NDVI, albedo, and LST. The monthly average spatial maps were then averaged over the areas affected by the Camp Fire to compute monthly mean values. This dataset is the Albedo WSA difference portion of that analysis.", + "extent": { + "spatial": { + "bbox": [ + [ + -121.78011150193434, + 39.59830951410488, + -121.35341172160868, + 39.89994756050158 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2015-01-01T00:00:00Z", + "2022-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "providers": [ + { + "name": "NASA EIS", + "url": "https://www.earthdata.nasa.gov/eis/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mike Newbry](https://unsplash.com/photos/DwtX9mMHBJ0) (Engulfed hillside in California, 2021)", + "href": "https://thumbnails.openveda.cloud/camp-fire-background.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/campfire-lst-day-diff.json b/ingestion-data/production/collections_new_metadata/campfire-lst-day-diff.json new file mode 100644 index 0000000..f59c270 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/campfire-lst-day-diff.json @@ -0,0 +1,72 @@ +{ + "id": "campfire-lst-day-diff", + "type": "Collection", + "title": "Camp Fire Domain: MODIS LST Day Difference", + "links": [], + "description": "3-year average difference (2018-2022) - (2015-2018) MODIS-derived LST Day over the 2018 Camp Fire burn scar domain. \n\n ### Technical Details \n\n In order to examine how the fire event affected the changes in surface properties, we utilized the MODIS-derived Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) products for a six-year period centered on the Camp Fire event (2015-2022). We used these products which are available at 16-day intervals to compute monthly averaged spatial maps of NDVI, albedo, and LST. The monthly average spatial maps were then averaged over the areas affected by the Camp Fire to compute monthly mean values. This dataset is the LST Day difference portion of that analysis.", + "extent": { + "spatial": { + "bbox": [ + [ + -121.78460307847297, + 39.59483467430542, + -121.35341172149457, + 39.89994756059251 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2015-01-01T00:00:00Z", + "2022-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "providers": [ + { + "name": "NASA EIS", + "url": "https://www.earthdata.nasa.gov/eis/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mike Newbry](https://unsplash.com/photos/DwtX9mMHBJ0) (Engulfed hillside in California, 2021)", + "href": "https://thumbnails.openveda.cloud/camp-fire-background.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/campfire-lst-night-diff.json b/ingestion-data/production/collections_new_metadata/campfire-lst-night-diff.json new file mode 100644 index 0000000..f4bba7e --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/campfire-lst-night-diff.json @@ -0,0 +1,72 @@ +{ + "id": "campfire-lst-night-diff", + "type": "Collection", + "title": "Camp Fire Domain: MODIS LST Night Difference", + "links": [], + "description": "3-year average difference (2018-2022) - (2015-2018) MODIS-derived LST Night over the 2018 Camp Fire burn scar domain. \n\n ### Technical Details \n\n In order to examine how the fire event affected the changes in surface properties, we utilized the MODIS-derived Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) products for a six-year period centered on the Camp Fire event (2015-2022). We used these products which are available at 16-day intervals to compute monthly averaged spatial maps of NDVI, albedo, and LST. The monthly average spatial maps were then averaged over the areas affected by the Camp Fire to compute monthly mean values. This dataset is the LST Night difference portion of that analysis.", + "extent": { + "spatial": { + "bbox": [ + [ + -121.78460307847297, + 39.59483467430542, + -121.35341172149457, + 39.89994756059251 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2015-01-01T00:00:00Z", + "2022-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "providers": [ + { + "name": "NASA EIS", + "url": "https://www.earthdata.nasa.gov/eis/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mike Newbry](https://unsplash.com/photos/DwtX9mMHBJ0) (Engulfed hillside in California, 2021)", + "href": "https://thumbnails.openveda.cloud/camp-fire-background.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/campfire-ndvi-diff.json b/ingestion-data/production/collections_new_metadata/campfire-ndvi-diff.json new file mode 100644 index 0000000..f36098d --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/campfire-ndvi-diff.json @@ -0,0 +1,72 @@ +{ + "id": "campfire-ndvi-diff", + "type": "Collection", + "title": "Camp Fire Domain: MODIS NDVI Difference", + "links": [], + "description": "3-year average difference (2018-2022) - (2015-2018) MODIS-derived NDVI over the 2018 Camp Fire burn scar domain. \n\n ### Technical Details \n\n In order to examine how the fire event affected the changes in surface properties, we utilized the MODIS-derived Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) products for a six-year period centered on the Camp Fire event (2015-2022). We used these products which are available at 16-day intervals to compute monthly averaged spatial maps of NDVI, albedo, and LST. The monthly average spatial maps were then averaged over the areas affected by the Camp Fire to compute monthly mean values. This dataset is the NDVI difference portion of that analysis.", + "extent": { + "spatial": { + "bbox": [ + [ + -121.78460307847297, + 39.59483467430542, + -121.35341172149457, + 39.89994756059251 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2015-01-01T00:00:00Z", + "2022-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "providers": [ + { + "name": "NASA EIS", + "url": "https://www.earthdata.nasa.gov/eis/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mike Newbry](https://unsplash.com/photos/DwtX9mMHBJ0) (Engulfed hillside in California, 2021)", + "href": "https://thumbnails.openveda.cloud/camp-fire-background.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/campfire-nlcd.json b/ingestion-data/production/collections_new_metadata/campfire-nlcd.json new file mode 100644 index 0000000..39014ed --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/campfire-nlcd.json @@ -0,0 +1,72 @@ +{ + "id": "campfire-nlcd", + "type": "Collection", + "title": "Camp Fire Domain: Land Cover", + "links": [], + "description": "30 meter LULC classification provided by the NLCD. \n\n ### Technical Details \n\n We utilized the National Land Cover Database (NLCD), which provides a classification of land cover categories at 30m spatial resolution over geographical locations within the Continental United States (CONUS). The NLCD is derived from Landsat satellite sensors data and is available at approximately three-year time intervals. We used the NLCD maps for the years 2016 and 2019 to examine changes in land cover type resulting from the Camp Fire event, to examine LULC before and after the Camp Fire. This analysis shows that the dominant vegetation cover type that was present within the region per-wildfire are evergreen forest and shrub/scrub cover, while post-wildfire are grasslands and herbaceous vegetation.", + "extent": { + "spatial": { + "bbox": [ + [ + -123.01078638251661, + 38.70177659870423, + -120.1714851176425, + 40.83029239162325 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2016-01-01T00:00:00Z", + "2019-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "providers": [ + { + "name": "NASA EIS", + "url": "https://www.earthdata.nasa.gov/eis/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mike Newbry](https://unsplash.com/photos/DwtX9mMHBJ0) (Engulfed hillside in California, 2021)", + "href": "https://thumbnails.openveda.cloud/camp-fire-background.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/co2-diff.json b/ingestion-data/production/collections_new_metadata/co2-diff.json new file mode 100644 index 0000000..759d1a5 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/co2-diff.json @@ -0,0 +1,88 @@ +{ + "id": "co2-diff", + "type": "Collection", + "title": "CO₂ (Diff)", + "links": [], + "description": "The changes in carbon dioxide (CO₂) levels in our atmosphere versus previous years. \n\n ### Technical Details \n\n The Impact of the COVID-19 Pandemic on Atmospheric CO2", + "extent": { + "spatial": { + "bbox": [ + [ + -180.3125, + -90.25, + 179.6875, + 90.25 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2015-01-01T00:00:00Z", + "2022-02-13T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "coolwarm", + "rescale": [ + [ + -1.5e-06, + 1.5e-06 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA", + "url": "https://science.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Marek Piwnicki](https://unsplash.com/photos/WiZOyYqzUss) (Power plant shooting steam at the sky)", + "href": "https://thumbnails.openveda.cloud/co2--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/co2-mean.json b/ingestion-data/production/collections_new_metadata/co2-mean.json new file mode 100644 index 0000000..5a87c2a --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/co2-mean.json @@ -0,0 +1,88 @@ +{ + "id": "co2-mean", + "type": "Collection", + "title": "CO₂ (Avg)", + "links": [], + "description": "The average background concentration of carbon dioxide (CO₂) in our atmosphere. \n\n ### Technical Details \n\n The Impact of the COVID-19 Pandemic on Atmospheric CO2", + "extent": { + "spatial": { + "bbox": [ + [ + -180.3125, + -90.25, + 179.6875, + 90.25 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2015-01-01T00:00:00Z", + "2022-02-13T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rdylbu_r", + "rescale": [ + [ + 0.000408, + 0.000419 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA", + "url": "https://science.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Marek Piwnicki](https://unsplash.com/photos/WiZOyYqzUss) (Power plant shooting steam at the sky)", + "href": "https://thumbnails.openveda.cloud/co2--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/combined_CMIP6_daily_GISS-E2-1-G_tas_kerchunk_DEMO.json b/ingestion-data/production/collections_new_metadata/combined_CMIP6_daily_GISS-E2-1-G_tas_kerchunk_DEMO.json new file mode 100644 index 0000000..e7a907c --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/combined_CMIP6_daily_GISS-E2-1-G_tas_kerchunk_DEMO.json @@ -0,0 +1,128 @@ +{ + "id": "combined_CMIP6_daily_GISS-E2-1-G_tas_kerchunk_DEMO", + "type": "Collection", + "title": "CMIP6 Daily GISS-E2-1-G TAS Kerchunk (DEMO)", + "links": [], + "description": "Historical (1950-2014) daily-mean near-surface (usually, 2 meter) air temperature in Kelvin. \n\n ### Technical Details \n\n * Format: [kerchunk (metadata)](https://fsspec.github.io/kerchunk/) for netCDF4 * Spatial Coverage: 180° W to 180° E, 60° S to 90° N * Temporal: 1950-01-01 to 1951-12-31 * _As noted below, this dataset is a subset all available data. The full dataset includes data from 1950 to 2100._ * Data Resolution: * Latitude Resolution: 0.25 degrees (25 km) * Longitude Resolution: 0.25 degrees (25 km) * Temporal Resolution: daily", + "assets": { + "zarr": { + "href": "s3://veda-data-store-staging/cmip6-GISS-E2-1-G-tas-kerchunk/combined_CMIP6_daily_GISS-E2-1-G_tas_kerchunk.json", + "type": "application/vnd+zarr", + "roles": [ + "data" + ], + "title": "zarr" + }, + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA (CMIP6 Near-Surface Air Temperature Screenshot)", + "href": "https://thumbnails.openveda.cloud/cmip6-tas.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + }, + "extent": { + "spatial": { + "bbox": [ + [ + 0.0, + -59.0, + 359.0, + 89.0 + ] + ] + }, + "temporal": { + "interval": [ + [ + "1950-01-01T12:00:00Z", + "2014-12-31T12:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/datacube/v2.0.0/schema.json" + ], + "data_type": "zarr", + "collection": "combined_CMIP6_daily_GISS-E2-1-G_tas_kerchunk_DEMO", + "cube:variables": { + "tas": { + "type": "data", + "unit": "K", + "attrs": { + "units": "K", + "comment": "near-surface (usually, 2 meter) air temperature; derived from downscaled tasmax & tasmin", + "long_name": "Daily Near-Surface Air Temperature", + "cell_methods": "area: mean time: maximum", + "standard_name": "air_temperature" + }, + "shape": [ + 23725, + 600, + 1440 + ], + "dimensions": [ + "time", + "lat", + "lon" + ], + "description": "Daily Near-Surface Air Temperature" + } + }, + "cube:dimensions": { + "lat": { + "axis": "y", + "step": 0.25, + "type": "spatial", + "extent": [ + -59.875, + 89.875 + ], + "description": "latitude", + "reference_system": 4326 + }, + "lon": { + "axis": "x", + "step": 0.25, + "type": "spatial", + "extent": [ + 0.125, + 359.875 + ], + "description": "longitude", + "reference_system": 4326 + }, + "time": { + "step": "P1DT0H0M0S", + "type": "temporal", + "extent": [ + "1950-01-01T12:00:00Z", + "2014-12-31T12:00:00Z" + ], + "description": "time" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "providers": [ + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ] +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/conus-reach.json b/ingestion-data/production/collections_new_metadata/conus-reach.json new file mode 100644 index 0000000..d5cfd2b --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/conus-reach.json @@ -0,0 +1,96 @@ +{ + "id": "conus-reach", + "type": "Collection", + "title": "Stream network across the Contiguous United States", + "links": [], + "description": "This dataset describes the Stream network across the Contiguous United States delineated using Soil and Water Assessment Tool \n\n ### Technical Details \n\n This dataset describes the Stream network across the Contiguous United States delineated using Soil and Water Assessment Tool", + "extent": { + "spatial": { + "bbox": [ + [ + -124.70647662199997, + 25.341586347000028, + -67.14524092289997, + 49.32899588910003 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2020-01-01T00:00:00Z", + "2020-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "gnbu_r", + "rescale": [ + [ + 1, + 1 + ] + ], + "nodata": 65535, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA EIS", + "url": "https://www.earthdata.nasa.gov/eis/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://www.nasa.gov) (A map showing nitrate loads in the rivers of the United States on 07/01/2018)", + "href": "https://thumbnails.openveda.cloud/CONUS_Nitrate_07012018.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/damage_probability_2022-10-03.json b/ingestion-data/production/collections_new_metadata/damage_probability_2022-10-03.json new file mode 100644 index 0000000..1a9bb7f --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/damage_probability_2022-10-03.json @@ -0,0 +1,91 @@ +{ + "id": "damage_probability_2022-10-03", + "type": "Collection", + "links": [], + "title": "Damage Probability Derived from UCONN GERs Lab After Hurricane Ian", + "extent": { + "spatial": { + "bbox": [ + [ + -82.376311139036, + 26.3117385950749, + -81.5589711806718, + 27.0376515475538 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2022-10-03T00:00:00+00:00", + "2022-10-03T23:59:59+00:00" + ] + ] + } + }, + "license": "CC0-1.0", + "providers": [ + { + "name": "UCONN NRE", + "url": "https://nre.uconn.edu/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "description": "DPI values from 0 to 99. 0: no damage; 99: damage mostly likely \n\n ### Technical Details \n\n Maximum Fire Radiative Power recorded by the Suomi NPP VIIRS sensor per 12hr fire line segment for the Thomas Fire of 2017", + "assets": { + "thumbnail": { + "href": "https://thumbnails.openveda.cloud/HLS_Damage_Probability_Cover_Image_FL.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ], + "title": "Thumbnail", + "description": "Photo by [CONUS Disturbance Watcher](https://gers.users.earthengine.app/view/nrt-conus) (Satellite imagery over Florida showing damage probability (using Viridis color ramp, with yellow being high probability and purple being low probability) for Oct 3, 2023)" + } + }, + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "magma", + "rescale": [ + [ + 0, + 99 + ] + ], + "bidx": [ + 1 + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "dashboard:is_periodic": true, + "dashboard:time_density": "day" +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/darnah-flood.json b/ingestion-data/production/collections_new_metadata/darnah-flood.json new file mode 100644 index 0000000..6bff234 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/darnah-flood.json @@ -0,0 +1,85 @@ +{ + "id": "darnah-flood", + "type": "Collection", + "links": [], + "title": "False Color Pre and Post Flood", + "assets": { + "thumbnail": { + "href": "https://thumbnails.openveda.cloud/darnah-flood-background.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ], + "title": "Thumbnail", + "description": "Photo by Marwan Alfaituri (Reuters)](https://abcnews.go.com/International/casualties-libya-floods-avoided-world-meteorological-organization-chief/story?id=103200104) (Satellite imagery over Florida showing damage probability (Aerial view over the Wadi Darnah River post-flood in Derna, Libya on September 14, 2023)" + } + }, + "extent": { + "spatial": { + "bbox": [ + [ + 22.063841231299286, + 32.42935916114897, + 23.256368419576482, + 33.43490918842431 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2023-09-07 00:00:00+00:00", + "2023-09-22 23:59:59+00:00" + ] + ] + } + }, + "license": "CC0-1.0", + "providers": [ + { + "url": "https://www.earthdata.nasa.gov/dashboard/", + "name": "NASA VEDA", + "roles": [ + "host" + ] + } + ], + "renders": { + "dashboard": { + "colormap_name": "magma", + "resampling": "bilinear", + "rescale": [ + [ + 0, + 5000 + ] + ], + "bidx": [ + 1 + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "description": "HLS falsecolor composite imagery using S30 Bands 12, 8A, and 4, over Darnah, Libya. \n\n ### Technical Details \n\n In order to examine how the fire event affected the changes in surface properties, we utilized the MODIS-derived Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) products for a six-year period centered on the Camp Fire event (2015-2022). We used these products which are available at 16-day intervals to compute monthly averaged spatial maps of NDVI, albedo, and LST. The monthly average spatial maps were then averaged over the areas affected by the Camp Fire to compute monthly mean values. This dataset is the LST Day difference portion of that analysis.", + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "stac_version": "1.0.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "dashboard:is_periodic": true, + "dashboard:time_density": "day" +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/darnah-gpm-daily.json b/ingestion-data/production/collections_new_metadata/darnah-gpm-daily.json new file mode 100644 index 0000000..c2e37e4 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/darnah-gpm-daily.json @@ -0,0 +1,86 @@ +{ + "id": "darnah-gpm-daily", + "type": "Collection", + "links": [], + "title": "GPM IMERG data of 2023 Medicane Daniel", + "assets": { + "thumbnail": { + "href": "https://thumbnails.openveda.cloud/darnah-flood-background.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ], + "title": "Thumbnail", + "description": "Photo by Marwan Alfaituri (Reuters)](https://abcnews.go.com/International/casualties-libya-floods-avoided-world-meteorological-organization-chief/story?id=103200104) (Satellite imagery over Florida showing damage probability (Aerial view over the Wadi Darnah River post-flood in Derna, Libya on September 14, 2023)" + } + }, + "extent": { + "spatial": { + "bbox": [ + [ + -10.06113118213864, + 14.912033716384059, + 45.00559573438803, + 48.50902534245416 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2023-09-04 00:00:00+00:00", + "2023-09-16 00:00:00+00:00" + ] + ] + } + }, + "license": "CC0-1.0", + "providers": [ + { + "url": "https://www.earthdata.nasa.gov/dashboard/", + "name": "NASA VEDA", + "roles": [ + "host" + ] + } + ], + "renders": { + "dashboard": { + "colormap_name": "inferno", + "nodata": 0, + "resampling": "bilinear", + "rescale": [ + [ + 0.1, + 500 + ] + ], + "bidx": [ + 1 + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "description": "Accumulated Rainfall (mm) over the eastern Mediterranean Sea from Medicane Daniel (4 - 16 September, 2023). \n\n ### Technical Details \n\n In order to examine how the fire event affected the changes in surface properties, we utilized the MODIS-derived Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) products for a six-year period centered on the Camp Fire event (2015-2022). We used these products which are available at 16-day intervals to compute monthly averaged spatial maps of NDVI, albedo, and LST. The monthly average spatial maps were then averaged over the areas affected by the Camp Fire to compute monthly mean values. This dataset is the LST Day difference portion of that analysis.", + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "stac_version": "1.0.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "dashboard:is_periodic": true, + "dashboard:time_density": "day" +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/disalexi-etsuppression.json b/ingestion-data/production/collections_new_metadata/disalexi-etsuppression.json new file mode 100644 index 0000000..6c27595 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/disalexi-etsuppression.json @@ -0,0 +1,89 @@ +{ + "id": "disalexi-etsuppression", + "type": "Collection", + "title": "disalexi-etsuppression", + "links": [], + "description": "Standardized ET anomaly using DisALEXI model of OpenET observations for 2017-20 fires, calculated as the difference of ET in the immediate post-fire water year from ET in the immediate pre-fire water year. The difference is normalized by pre-fire ET and negative values denote vegetation disturbance induced by fire or by a climatological anomaly resulting in the decline in ET \n\n ### Technical Details \n\n Impact of fires on changes in evapotranspiration, obtained OpenET observations (DisALEXI model) for 2017-20 fires", + "extent": { + "spatial": { + "bbox": [ + [ + -125.35091474603803, + 29.833050585609307, + -108.1212275966256, + 49.03903136008468 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-01-01T00:00:00Z", + "2020-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "asset_bidx": "cog_default|1", + "colormap_name": "rdylbu", + "rescale": [ + [ + -1.0, + 1.0 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "MTBS", + "url": "https://www.mtbs.gov/project-overview", + "roles": [ + "producer" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mike Newbry](https://unsplash.com/photos/DwtX9mMHBJ0) (Hillside engulfed by wildfire)", + "href": "https://thumbnails.openveda.cloud/mtbs-burn-severity--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/ecco-surface-height-change.json b/ingestion-data/production/collections_new_metadata/ecco-surface-height-change.json new file mode 100644 index 0000000..ff8926b --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/ecco-surface-height-change.json @@ -0,0 +1,89 @@ +{ + "id": "ecco-surface-height-change", + "type": "Collection", + "title": "ECCO sea-surface height change from 1992 to 2017", + "links": [], + "description": "Gridded global sea-surface height change from 1992 to 2017 from the Estimating the Circulation and Climate of the Ocean (ECCO) ocean state estimate. \n\n ### Technical Details \n\n Gridded global sea-surface height change from 1992 to 2017 from the Estimating the Circulation and Climate of the Ocean (ECCO) ocean state estimate. The dataset was calculated as the difference between the annual means over 2017 and 1992, from the 0.5 degree, gridded monthly mean data product available on [PO.DAAC](https://podaac.jpl.nasa.gov/dataset/ECCO_L4_SSH_05DEG_MONTHLY_V4R4).", + "extent": { + "spatial": { + "bbox": [ + [ + -180, + -90, + 180, + 90 + ] + ] + }, + "temporal": { + "interval": [ + [ + "1992-01-01T00:00:00Z", + "2017-12-31T23:59:59Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rdbu", + "rescale": [ + [ + -0.313, + 0.313 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA JPL Physical Oceanography Distributed Active Archive Center (PODAAC)", + "url": "https://podaac.jpl.nasa.gov/dataset/ECCO_L4_SSH_05DEG_MONTHLY_V4R4", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host", + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Lance Asper](https://unsplash.com/photos/3P3NHLZGCp8) (Wave crashing on a sandy beach)", + "href": "https://thumbnails.openveda.cloud/ecco-surface-height-change--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/eis_fire_perimeter.json b/ingestion-data/production/collections_new_metadata/eis_fire_perimeter.json new file mode 100644 index 0000000..6602269 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/eis_fire_perimeter.json @@ -0,0 +1,86 @@ +{ + "id": "eis_fire_perimeter", + "type": "Collection", + "title": "Fire Perimeters", + "links": [ + { + "rel": "external", + "href": "https://firenrt.delta-backend.com/collections/public.eis_fire_snapshot_perimeter_nrt", + "type": "application/json", + "label:assets": null + } + ], + "description": "eis_fire_perimeter \n\n ### Technical Details \n\n Fire perimeter data is generated by the FEDs algorithm. The FEDs algorithm tracks fire movement and severity by ingesting observations from the VIIRS thermal sensors on the Suomi NPP and NOAA-20 satellites. This algorithm uses raw VIIRS observations to generate a polygon of the fire, locations of the active fire line, and estimates of fire mean Fire Radiative Power (FRP). The VIIRS sensors overpass at ~1:30 AM and PM local time, and provide estimates of fire evolution ~ every 12 hours. The data produced by this algorithm describe where fires are in space and how fires evolve through time. This CONUS-wide implementation of the FEDs algorithm is based on [Chen et al 2020’s algorithm for California.](https://www.nature.com/articles/s41597-022-01343-0)", + "extent": { + "spatial": { + "bbox": [ + [ + -171.791110603, + 18.91619, + -66.96466, + 71.3577635769 + ] + ] + }, + "temporal": { + "interval": [ + [ + null, + null + ] + ] + } + }, + "license": "public-domain", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "providers": [ + { + "name": "NOAA", + "url": "https://www.noaa.gov", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA Earth Information System", + "url": "https://www.earthdata.nasa.gov/eis", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Matt Howard](https://unsplash.com/photos/eAKDzK4lo4o) (Forest burning at night)", + "href": "https://thumbnails.openveda.cloud/fire--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/facebook_population_density.json b/ingestion-data/production/collections_new_metadata/facebook_population_density.json new file mode 100644 index 0000000..5d3c399 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/facebook_population_density.json @@ -0,0 +1,101 @@ +{ + "id": "facebook_population_density", + "type": "Collection", + "title": "Population Density Maps using satellite imagery built by Meta", + "links": [ + { + "rel": "external", + "href": "https://arxiv.org/pdf/1712.05839.pdf", + "type": "application/pdf", + "title": "Mapping the world population one building at a time" + } + ], + "description": "Facebook high-resolution population density with a 30m² resolution \n\n ### Technical Details \n\n In partnership with the Center for International Earth Science Information Network (CIESIN) at Columbia University, Meta [formerly known as Facebook] used census data and computer vision techniques (Convolutional Neural Networks) to identify buildings from publicly accessible mapping services to create population density datasets. These high-resolution maps estimate the number of individuals living within 30-meter grid tiles on a global scale. The population estimates are based on data from the Gridded Population of the World (GPWv4) data collection.", + "extent": { + "spatial": { + "bbox": [ + [ + -180.00041666666667, + -55.985972222324634, + 179.82041666695605, + 71.33069444444443 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2015-01-01T00:00:00Z", + "2015-01-01T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "ylorrd", + "rescale": [ + [ + 0, + 69 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "Meta Data for Good", + "url": "https://dataforgood.facebook.com/dfg/tools/high-resolution-population-density-maps", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA (2015 high resolution population density for Paris)", + "href": "https://thumbnails.openveda.cloud/fb-population--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/fldas-soil-moisture-anomalies.json b/ingestion-data/production/collections_new_metadata/fldas-soil-moisture-anomalies.json new file mode 100644 index 0000000..51ab226 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/fldas-soil-moisture-anomalies.json @@ -0,0 +1,93 @@ +{ + "id": "fldas-soil-moisture-anomalies", + "type": "Collection", + "title": "FLDAS Surface Soil Moisture Anomalies", + "links": [], + "description": "Surface soil moisture 0-10cm anomaly \n\n ### Technical Details \n\n - **Temporal Extent:** January 1982 - June 2023 - **Temporal Resolution:** Monthly - **Spatial Extent:** Quasi-Global ( -180.0,-60.0,180.0,90.0) - **Spatial Resolution:** 10 km x 10 km - **Data Units:** Fraction Soil moisture anomaly (mm3/mm3) difference from 1982-2016 monthly mean - **Data Type:** Research - **Data Latency:** Monthly", + "extent": { + "spatial": { + "bbox": [ + [ + -180, + -60, + 180, + 90 + ] + ] + }, + "temporal": { + "interval": [ + [ + "1982-01-01T00:00:00Z", + "2023-07-01T00:00:00Z" + ] + ] + } + }, + "license": "not-provided", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rdbu", + "rescale": [ + [ + -0.3, + 0.3 + ] + ], + "resampling": "bilinear", + "bidx": [ + 1 + ], + "nodata": -9999, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA", + "url": "https://nasa.gov", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by Amy McNally (Landscape in Gondar, Ethiopia)", + "href": "https://thumbnails.openveda.cloud/FLDAS_Dataset_Cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/frp-max-thomasfire.json b/ingestion-data/production/collections_new_metadata/frp-max-thomasfire.json new file mode 100644 index 0000000..a0593f2 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/frp-max-thomasfire.json @@ -0,0 +1,97 @@ +{ + "id": "frp-max-thomasfire", + "type": "Collection", + "title": "Maximum Fire Radiative Power for Thomas Fire", + "links": [], + "description": "Maximum Fire Radiative Power recorded by the Suomi NPP VIIRS sensor per 12hr fire line segment for the Thomas Fire of 2017 \n\n ### Technical Details \n\n Maximum Fire Radiative Power recorded by the Suomi NPP VIIRS sensor per 12hr fire line segment for the Thomas Fire of 2017", + "extent": { + "spatial": { + "bbox": [ + [ + -119.7279834250452, + 34.19572604525683, + -118.88724142537933, + 34.72668711929945 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-12-01T00:00:00Z", + "2017-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "asset_bidx": "cog_default|1", + "colormap_name": "inferno_r", + "rescale": [ + [ + 1.0, + 1080 + ] + ], + "nodata": "nan", + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS Burnt Area Emergency Response (BAER)", + "url": "https://burnseverity.cr.usgs.gov/products/baer", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mike Newbry](https://unsplash.com/photos/DwtX9mMHBJ0) (Hillside engulfed by wildfire)", + "href": "https://thumbnails.openveda.cloud/mtbs-burn-severity--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/geoglam.json b/ingestion-data/production/collections_new_metadata/geoglam.json new file mode 100644 index 0000000..15488c7 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/geoglam.json @@ -0,0 +1,127 @@ +{ + "id": "geoglam", + "type": "Collection", + "title": "GEOGLAM Crop Monitor", + "links": [], + "description": "Combined crop conditions across both the Crop Monitor for AMIS and Crop Monitor for Early Warning \n\n ### Technical Details \n\n The Group on Earth Observation's Global Agricultural Monitoring Initiative (GEOGLAM) Global Crop Monitor uses remote sensing data like global precipitation and soil moisture measurements to help reduce uncertainty, promote market transparency, and provide early warning for crop failures through multi-agency collaboration.", + "extent": { + "spatial": { + "bbox": [ + [ + -180.004464285715, + -90, + 180.00611292773385, + 90 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2020-01-01T00:00:00Z", + "2023-06-01T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap": { + "1": [ + 120, + 120, + 120 + ], + "2": [ + 130, + 65, + 0 + ], + "3": [ + 66, + 207, + 56 + ], + "4": [ + 245, + 239, + 0 + ], + "5": [ + 241, + 89, + 32 + ], + "6": [ + 168, + 0, + 0 + ], + "7": [ + 0, + 143, + 201 + ] + }, + "bidx": [ + 1 + ], + "unscale": false, + "resampling": "nearest", + "max_size": 1024, + "return_mask": true, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USDA & Global Crop Monitor Group partners", + "url": "https://data.nal.usda.gov/dataset/geoglam-geo-global-agricultural-monitoring-crop-assessment-tool#:~:text=The%20GEOGLAM%20crop%20calendars%20are,USDA%20FAS%2C%20and%20USDA%20NASS.", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Jean Wimmerlin](https://unsplash.com/photos/RUj5b4YXaHE) (Bird's eye view of fields)", + "href": "https://thumbnails.openveda.cloud/geoglam--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/grdi-cdr-raster.json b/ingestion-data/production/collections_new_metadata/grdi-cdr-raster.json new file mode 100644 index 0000000..5837c16 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/grdi-cdr-raster.json @@ -0,0 +1,90 @@ +{ + "id": "grdi-cdr-raster", + "type": "Collection", + "title": "GRDI CDR Constituent Raster", + "links": [], + "description": "Global Gridded Relative Deprivation Index (GRDI) Child Dependency Ratio (CDR) Constituent raster \n\n ### Technical Details \n\n The Global Gridded Relative Deprivation Index (GRDI), Version 1 (GRDIv1) dataset characterizes the relative levels of multidimensional deprivation and poverty in each 30 arc-second (~1 km) pixel, where a value of 100 represents the highest level of deprivation and a value of 0 the lowest. GRDIv1 is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into six main components to produce the final index raster. Inputs were selected from the best-available data that either continuously vary across space or have at least administrative level 1 (provincial/state) resolution, and which have global spatial coverage.", + "extent": { + "spatial": { + "bbox": [ + [ + -179.99999999990004, + -55.983333333466476, + 179.81666666676645, + 82.18333333320012 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2010-01-01T00:00:00Z", + "2010-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "viridis", + "rescale": [ + [ + 0, + 100 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA CIESIN", + "url": "https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Jordan Opel](https://unsplash.com/photos/3VLHF9b9Plg) (Shacks along a river almost collapsing)", + "href": "https://thumbnails.openveda.cloud/grdi--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/grdi-filled-missing-values-count.json b/ingestion-data/production/collections_new_metadata/grdi-filled-missing-values-count.json new file mode 100644 index 0000000..1136471 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/grdi-filled-missing-values-count.json @@ -0,0 +1,90 @@ +{ + "id": "grdi-filled-missing-values-count", + "type": "Collection", + "title": "GRDI Filled Missing Values Count", + "links": [], + "description": "Global Gridded Relative Deprivation Index (GRDI) raster showing count of constituent inputs that were filled in per cell using the Fill Missing Values tool. \n\n ### Technical Details \n\n The Global Gridded Relative Deprivation Index (GRDI), Version 1 (GRDIv1) dataset characterizes the relative levels of multidimensional deprivation and poverty in each 30 arc-second (~1 km) pixel, where a value of 100 represents the highest level of deprivation and a value of 0 the lowest. GRDIv1 is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into six main components to produce the final index raster. Inputs were selected from the best-available data that either continuously vary across space or have at least administrative level 1 (provincial/state) resolution, and which have global spatial coverage.", + "extent": { + "spatial": { + "bbox": [ + [ + -180, + -55.983333333333334, + 179.81666666666666, + 82.18333333333332 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2010-01-01T00:00:00Z", + "2021-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "viridis", + "rescale": [ + [ + 1, + 2 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA CIESIN", + "url": "https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Jordan Opel](https://unsplash.com/photos/3VLHF9b9Plg) (Shacks along a river almost collapsing)", + "href": "https://thumbnails.openveda.cloud/grdi--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/grdi-imr-raster.json b/ingestion-data/production/collections_new_metadata/grdi-imr-raster.json new file mode 100644 index 0000000..4c53773 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/grdi-imr-raster.json @@ -0,0 +1,90 @@ +{ + "id": "grdi-imr-raster", + "type": "Collection", + "title": "GRDI IMR Constituent Raster", + "links": [], + "description": "Global Gridded Relative Deprivation Index (GRDI) Infant Mortality Rate (IMR) Constituent raster \n\n ### Technical Details \n\n The Global Gridded Relative Deprivation Index (GRDI), Version 1 (GRDIv1) dataset characterizes the relative levels of multidimensional deprivation and poverty in each 30 arc-second (~1 km) pixel, where a value of 100 represents the highest level of deprivation and a value of 0 the lowest. GRDIv1 is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into six main components to produce the final index raster. Inputs were selected from the best-available data that either continuously vary across space or have at least administrative level 1 (provincial/state) resolution, and which have global spatial coverage.", + "extent": { + "spatial": { + "bbox": [ + [ + -179.99999999990004, + -55.983333333466476, + 179.81666666643937, + 82.18333333307453 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2015-01-01T00:00:00Z", + "2015-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "viridis", + "rescale": [ + [ + 0, + 100 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA CIESIN", + "url": "https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Jordan Opel](https://unsplash.com/photos/3VLHF9b9Plg) (Shacks along a river almost collapsing)", + "href": "https://thumbnails.openveda.cloud/grdi--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/grdi-shdi-raster.json b/ingestion-data/production/collections_new_metadata/grdi-shdi-raster.json new file mode 100644 index 0000000..fb4a021 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/grdi-shdi-raster.json @@ -0,0 +1,90 @@ +{ + "id": "grdi-shdi-raster", + "type": "Collection", + "title": "GRDI SHDI Constituent Raster", + "links": [], + "description": "Global Gridded Relative Deprivation Index (GRDI) Subnational Human Development Index (SHDI) Constituent raster \n\n ### Technical Details \n\n The Global Gridded Relative Deprivation Index (GRDI), Version 1 (GRDIv1) dataset characterizes the relative levels of multidimensional deprivation and poverty in each 30 arc-second (~1 km) pixel, where a value of 100 represents the highest level of deprivation and a value of 0 the lowest. GRDIv1 is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into six main components to produce the final index raster. Inputs were selected from the best-available data that either continuously vary across space or have at least administrative level 1 (provincial/state) resolution, and which have global spatial coverage.", + "extent": { + "spatial": { + "bbox": [ + [ + -179.99999999990004, + -55.983333333466476, + 179.81666666676645, + 82.18333333320012 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2018-01-01T00:00:00Z", + "2018-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "viridis", + "rescale": [ + [ + 0, + 100 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA CIESIN", + "url": "https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Jordan Opel](https://unsplash.com/photos/3VLHF9b9Plg) (Shacks along a river almost collapsing)", + "href": "https://thumbnails.openveda.cloud/grdi--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/grdi-v1-built.json b/ingestion-data/production/collections_new_metadata/grdi-v1-built.json new file mode 100644 index 0000000..bb79e7f --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/grdi-v1-built.json @@ -0,0 +1,90 @@ +{ + "id": "grdi-v1-built", + "type": "Collection", + "title": "GRDI BUILT Constituent Raster", + "links": [], + "description": "Global Gridded Relative Deprivation Index (GRDI) built-up area (BUILT) Constituent raster, indexed 0 to 100 \n\n ### Technical Details \n\n The Global Gridded Relative Deprivation Index (GRDI), Version 1 (GRDIv1) dataset characterizes the relative levels of multidimensional deprivation and poverty in each 30 arc-second (~1 km) pixel, where a value of 100 represents the highest level of deprivation and a value of 0 the lowest. GRDIv1 is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into six main components to produce the final index raster. Inputs were selected from the best-available data that either continuously vary across space or have at least administrative level 1 (provincial/state) resolution, and which have global spatial coverage.", + "extent": { + "spatial": { + "bbox": [ + [ + -179.99999999990004, + -55.983333333466476, + 179.81666666676645, + 82.18333333320012 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2015-01-01T00:00:00Z", + "2021-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "viridis", + "rescale": [ + [ + 0, + 100 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA CIESIN", + "url": "https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Jordan Opel](https://unsplash.com/photos/3VLHF9b9Plg) (Shacks along a river almost collapsing)", + "href": "https://thumbnails.openveda.cloud/grdi--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/grdi-v1-raster.json b/ingestion-data/production/collections_new_metadata/grdi-v1-raster.json new file mode 100644 index 0000000..e59c8ad --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/grdi-v1-raster.json @@ -0,0 +1,90 @@ +{ + "id": "grdi-v1-raster", + "type": "Collection", + "title": "GRDI V1 raster", + "links": [], + "description": "Global Gridded Relative Deprivation Index (GRDI), V1 raster \n\n ### Technical Details \n\n The Global Gridded Relative Deprivation Index (GRDI), Version 1 (GRDIv1) dataset characterizes the relative levels of multidimensional deprivation and poverty in each 30 arc-second (~1 km) pixel, where a value of 100 represents the highest level of deprivation and a value of 0 the lowest. GRDIv1 is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into six main components to produce the final index raster. Inputs were selected from the best-available data that either continuously vary across space or have at least administrative level 1 (provincial/state) resolution, and which have global spatial coverage.", + "extent": { + "spatial": { + "bbox": [ + [ + -179.99999999990004, + -55.983333333466476, + 179.81666666676645, + 82.18333333320012 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2010-01-01T00:00:00Z", + "2021-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "viridis", + "rescale": [ + [ + 0, + 100 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA CIESIN", + "url": "https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Jordan Opel](https://unsplash.com/photos/3VLHF9b9Plg) (Shacks along a river almost collapsing)", + "href": "https://thumbnails.openveda.cloud/grdi--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/grdi-vnl-raster.json b/ingestion-data/production/collections_new_metadata/grdi-vnl-raster.json new file mode 100644 index 0000000..d7db7fe --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/grdi-vnl-raster.json @@ -0,0 +1,90 @@ +{ + "id": "grdi-vnl-raster", + "type": "Collection", + "title": "GRDI VNL Constituent Raster", + "links": [], + "description": "Global Gridded Relative Deprivation Index (GRDI) VIIRS Night Lights (VNL) Constituent raster \n\n ### Technical Details \n\n The Global Gridded Relative Deprivation Index (GRDI), Version 1 (GRDIv1) dataset characterizes the relative levels of multidimensional deprivation and poverty in each 30 arc-second (~1 km) pixel, where a value of 100 represents the highest level of deprivation and a value of 0 the lowest. GRDIv1 is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into six main components to produce the final index raster. Inputs were selected from the best-available data that either continuously vary across space or have at least administrative level 1 (provincial/state) resolution, and which have global spatial coverage.", + "extent": { + "spatial": { + "bbox": [ + [ + -179.99999999990004, + -55.983333333466476, + 179.81666666676645, + 82.18333333320012 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2020-01-01T00:00:00Z", + "2020-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "viridis", + "rescale": [ + [ + 0, + 100 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA CIESIN", + "url": "https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Jordan Opel](https://unsplash.com/photos/3VLHF9b9Plg) (Shacks along a river almost collapsing)", + "href": "https://thumbnails.openveda.cloud/grdi--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/grdi-vnl-slope-raster.json b/ingestion-data/production/collections_new_metadata/grdi-vnl-slope-raster.json new file mode 100644 index 0000000..01a6d24 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/grdi-vnl-slope-raster.json @@ -0,0 +1,90 @@ +{ + "id": "grdi-vnl-slope-raster", + "type": "Collection", + "title": "GRDI VNL Slope Constituent Raster", + "links": [], + "description": "Global Gridded Relative Deprivation Index (GRDI) VIIRS Night Lights (VNL) Slope Constituent raster \n\n ### Technical Details \n\n The Global Gridded Relative Deprivation Index (GRDI), Version 1 (GRDIv1) dataset characterizes the relative levels of multidimensional deprivation and poverty in each 30 arc-second (~1 km) pixel, where a value of 100 represents the highest level of deprivation and a value of 0 the lowest. GRDIv1 is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into six main components to produce the final index raster. Inputs were selected from the best-available data that either continuously vary across space or have at least administrative level 1 (provincial/state) resolution, and which have global spatial coverage.", + "extent": { + "spatial": { + "bbox": [ + [ + -179.99999999990004, + -55.983333333466476, + 179.81666666676645, + 82.18333333320012 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2012-01-01T00:00:00Z", + "2020-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "viridis", + "rescale": [ + [ + 0, + 100 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA CIESIN", + "url": "https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Jordan Opel](https://unsplash.com/photos/3VLHF9b9Plg) (Shacks along a river almost collapsing)", + "href": "https://thumbnails.openveda.cloud/grdi--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/hls-bais2-v2.json b/ingestion-data/production/collections_new_metadata/hls-bais2-v2.json new file mode 100644 index 0000000..65b9e19 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/hls-bais2-v2.json @@ -0,0 +1,79 @@ +{ + "id": "hls-bais2-v2", + "type": "Collection", + "title": "HLS-calculated BAIS2 burned area", + "links": [], + "description": "Experimental burned-area calculation from the HLS scene taken on August 13,2023 over Lahaina, HI \n\n ### Technical Details \n\n On August 8th, 2023, a devastating wildfire rapidly spread through the city of Lahaina, Hawai’i, which is located on the island of Maui and home to over 13,000 residents. This destructive wildfire was initially ignited by a downed powerline on Lahainaluna Road and was later fueled by intense wind gusts that persisted throughout the day. The National Weather Service recorded wind gusts as high as 67 mph in the area, contributing to the rapid spread of the wildfire across much of Lahaina during the afternoon hours of August 8th.", + "extent": { + "spatial": { + "bbox": [ + [ + -156.69638870402082, + 20.842046882739975, + -156.64345004018185, + 20.911820074106824 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2023-08-13T00:00:00Z", + "2023-08-13T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA", + "url": "https://hls.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Matthew Thayer/AP](https://www.sfchronicle.com/travel/article/hawaii-fire-maui-lahaina-18289213.php) (Wildfire erupting over Lahaina, HI, August 8, 2023)", + "href": "https://thumbnails.openveda.cloud/lahaina-fire-background.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/hls-entropy-difference.json b/ingestion-data/production/collections_new_metadata/hls-entropy-difference.json new file mode 100644 index 0000000..64fbd91 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/hls-entropy-difference.json @@ -0,0 +1,98 @@ +{ + "id": "hls-entropy-difference", + "type": "Collection", + "links": [], + "title": "HLS-derived entropy difference for Assessing impacts from Hurricane Ian", + "extent": { + "spatial": { + "bbox": [ + [ + -82.376311139036, + 26.3117385950749, + -81.9037040761012, + 27.0358376646312 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2022-09-30T00:00:00Z", + "2022-09-30T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA", + "url": "https://hls.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "description": "Bitemporal Different with higher values indicating higher likelihood of change from before to after Ian. \n\n ### Technical Details \n\n Nightlights data are collected by the [Visible Infrared Radiometer Suite (VIIRS) Day/Night Band (DNB)](https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/viirs/) on the Suomi-National Polar-Orbiting Partnership (Suomi-NPP) platform, a joint National Oceanic and Atmospheric Administration (NOAA) and NASA satellite. The images are produced by [NASA’s Black Marble](https://blackmarble.gsfc.nasa.gov/) products suite. All data are calibrated daily, corrected, and validated with ground measurements for science-ready analysis.", + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "bwr", + "rescale": [ + [ + -1, + 1 + ] + ], + "bidx": [ + 1 + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "dashboard:is_periodic": false, + "dashboard:time_density": "day", + "assets": { + "thumbnail": { + "href": "https://thumbnails.openveda.cloud/ian_goes_cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ], + "title": "Thumbnail", + "description": "Photo by [Joshua Stevens, using GOES 16 imagery courtesy of NESDIS](https://visibleearth.nasa.gov/images/150408/hurricane-ian-reaches-florida) (Hurricane Ian as seen from space as it makes landfall with the state of Florida. NASA Earth Observatory image.)" + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/hls-l30-002-ej-reprocessed.json b/ingestion-data/production/collections_new_metadata/hls-l30-002-ej-reprocessed.json new file mode 100644 index 0000000..e942cf4 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/hls-l30-002-ej-reprocessed.json @@ -0,0 +1,91 @@ +{ + "id": "hls-l30-002-ej-reprocessed", + "type": "Collection", + "title": "HLSL30.002 Environmental Justice Events", + "links": [ + { + "rel": "external", + "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2021957657-LPCLOUD.html", + "type": "text/html", + "title": "NASA Common Metadata Repository Record for this Dataset" + } + ], + "description": "Harmonized Landsat SWIR: small subset near Puerto Rico \n\n ### Technical Details \n\n Input data from Landsat 8/9 and Sentinel-2A/B is reprojected and Sentinel-2 data adjusted so that the output data products, HLSL30 (Landsat-derived) and HLSS30 (Sentinel-2-derived) can be used interchangeably. The harmonization of the Optical Land Imager (OLI) on Landsat 8/9 and Multispectral Imager (MSI) on Sentinel-2A/B increases the time series density of plot-scale observations such that data is available every 2-4 days over a given location.", + "extent": { + "spatial": { + "bbox": [ + [ + -90.932637, + 17.961538, + -65.110098, + 30.71627 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-06-06T14:43:41.335694Z", + "2021-10-21T16:32:32.165563Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json" + ], + "dashboard:is_periodic": false, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "post_process": "swir", + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + }, + { + "url": "https://lpdaac.usgs.gov/products/hlsl30v002/", + "name": "Land Processes Distributed Active Archive Center (LP DAAC)", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://nasa.gov) (2017 harmonized Landsat 8 shortwave infrared (SWIR) false color composite image that provides enhanced contrast to detect flood extent)", + "href": "https://thumbnails.openveda.cloud/hls-events-ej--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/hls-ndvi-difference.json b/ingestion-data/production/collections_new_metadata/hls-ndvi-difference.json new file mode 100644 index 0000000..9a06d34 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/hls-ndvi-difference.json @@ -0,0 +1,98 @@ +{ + "id": "hls-ndvi-difference", + "type": "Collection", + "links": [], + "title": "HLS-derived NDVI difference for Assessing Impacts from Hurricane Iann", + "extent": { + "spatial": { + "bbox": [ + [ + -82.376311139036, + 26.3117385950749, + -81.9037040761012, + 27.0358376646312 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2022-09-30T00:00:00Z", + "2022-09-30T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA", + "url": "https://hls.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "description": "NDVI Difference: -1 to 1; -1 = decrease in vegetation; 1 = increase in vegetation \n\n ### Technical Details \n\n Terrestrial water storage (TWS) is defined as the summation of all water on the land surface and in the subsurface. It includes surface soil moisture, root zone soil moisture, groundwater, snow, ice, water stored in the vegetation, river and lake water.", + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rdbu", + "rescale": [ + [ + -1, + 1 + ] + ], + "bidx": [ + 1 + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "dashboard:is_periodic": false, + "dashboard:time_density": "day", + "assets": { + "thumbnail": { + "href": "https://thumbnails.openveda.cloud/ian_goes_cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ], + "title": "Thumbnail", + "description": "Photo by [Joshua Stevens, using GOES 16 imagery courtesy of NESDIS](https://visibleearth.nasa.gov/images/150408/hurricane-ian-reaches-florida) (Hurricane Ian as seen from space as it makes landfall with the state of Florida. NASA Earth Observatory image.)" + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/hls-ndvi.json b/ingestion-data/production/collections_new_metadata/hls-ndvi.json new file mode 100644 index 0000000..94d5f08 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/hls-ndvi.json @@ -0,0 +1,79 @@ +{ + "id": "hls-ndvi", + "type": "Collection", + "title": "Normalized difference vegetation index from HLS", + "links": [], + "description": "NDVI: 0 to 1; 0 = little to no vegetation; 1 = heavy vegetation \n\n ### Technical Details \n\n Terrestrial water storage (TWS) is defined as the summation of all water on the land surface and in the subsurface. It includes surface soil moisture, root zone soil moisture, groundwater, snow, ice, water stored in the vegetation, river and lake water.", + "extent": { + "spatial": { + "bbox": [ + [ + -82.37631113903603, + 26.31173859507485, + -81.9037040761012, + 27.035837664631245 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2022-09-05T00:00:00Z", + "2022-09-05T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA", + "url": "https://hls.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA (Screenshot of harmonized landsat normalized difference vegetation index from September 2022)", + "href": "https://thumbnails.openveda.cloud/hls-ndvi.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/hls-s30-002-ej-reprocessed.json b/ingestion-data/production/collections_new_metadata/hls-s30-002-ej-reprocessed.json new file mode 100644 index 0000000..2538edd --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/hls-s30-002-ej-reprocessed.json @@ -0,0 +1,91 @@ +{ + "id": "hls-s30-002-ej-reprocessed", + "type": "Collection", + "title": "HLSS30.002 Environmental Justice Events", + "links": [ + { + "rel": "external", + "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2021957295-LPCLOUD.html", + "type": "text/html", + "title": "NASA Common Metadata Repository Record for this Dataset" + } + ], + "description": "Harmonized Sentinel-2 SWIR: small subset near Puerto Rico \n\n ### Technical Details \n\n Input data from Landsat 8/9 and Sentinel-2A/B is reprojected and Sentinel-2 data adjusted so that the output data products, HLSL30 (Landsat-derived) and HLSS30 (Sentinel-2-derived) can be used interchangeably. The harmonization of the Optical Land Imager (OLI) on Landsat 8/9 and Multispectral Imager (MSI) on Sentinel-2A/B increases the time series density of plot-scale observations such that data is available every 2-4 days over a given location.", + "extent": { + "spatial": { + "bbox": [ + [ + -90.932637, + 17.963773, + -65.110098, + 30.71627 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-07-12T15:07:20.450000Z", + "2021-10-27T16:55:17.997700Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json" + ], + "dashboard:is_periodic": false, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "post_process": "swir", + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + }, + { + "url": "https://lpdaac.usgs.gov/products/hlss30v002/", + "name": "Land Processes Distributed Active Archive Center (LP DAAC)", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://nasa.gov) (2017 harmonized Landsat 8 shortwave infrared (SWIR) false color composite image that provides enhanced contrast to detect flood extent)", + "href": "https://thumbnails.openveda.cloud/hls-events-ej--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/hls-swir-falsecolor-composite.json b/ingestion-data/production/collections_new_metadata/hls-swir-falsecolor-composite.json new file mode 100644 index 0000000..90ba10e --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/hls-swir-falsecolor-composite.json @@ -0,0 +1,79 @@ +{ + "id": "hls-swir-falsecolor-composite", + "type": "Collection", + "title": "HLS SWIR FalseColor Composite", + "links": [], + "description": "HLS falsecolor composite imagery using S30 Bands 12, 8A, and 4, over Lahaina, HI. \n\n ### Technical Details \n\n On August 8th, 2023, a devastating wildfire rapidly spread through the city of Lahaina, Hawai’i, which is located on the island of Maui and home to over 13,000 residents. This destructive wildfire was initially ignited by a downed powerline on Lahainaluna Road and was later fueled by intense wind gusts that persisted throughout the day. The National Weather Service recorded wind gusts as high as 67 mph in the area, contributing to the rapid spread of the wildfire across much of Lahaina during the afternoon hours of August 8th.", + "extent": { + "spatial": { + "bbox": [ + [ + -157.08006491221116, + 20.685657249416465, + -156.0067983462315, + 21.69215133711284 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2023-08-08T00:00:00Z", + "2023-08-13T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA", + "url": "https://hls.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Matthew Thayer/AP](https://www.sfchronicle.com/travel/article/hawaii-fire-maui-lahaina-18289213.php) (Wildfire erupting over Lahaina, HI, August 8, 2023)", + "href": "https://thumbnails.openveda.cloud/lahaina-fire-background.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/houston-aod-diff.json b/ingestion-data/production/collections_new_metadata/houston-aod-diff.json new file mode 100644 index 0000000..42a5d26 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/houston-aod-diff.json @@ -0,0 +1,96 @@ +{ + "id": "houston-aod-diff", + "type": "Collection", + "title": "Houston AOD: Difference Between 2000-2009 & 2010-2019", + "links": [], + "description": "This figure shows the difference in AOD in the form of a raster when subtracting the two decades from the original AOD Dataset \n\n ### Technical Details \n\n This dataset comes from the two decadal COGs that displayed mean Aerosol Optical Depth for 2000-2009 and for 2010-2019. Those tiffs were subtracted to display the differences between the two decades.", + "extent": { + "spatial": { + "bbox": [ + [ + -97.00906753206712, + 27.992675617599986, + -93.99072817742552, + 31.017446580357053 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2019-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "bwr", + "rescale": [ + [ + -0.1, + 0.1 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Nick van den Berg](https://unsplash.com/photos/2vb-_3t6YCM) (Smog Located In City)", + "href": "https://thumbnails.openveda.cloud/smog-city.png", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/houston-aod.json b/ingestion-data/production/collections_new_metadata/houston-aod.json new file mode 100644 index 0000000..88c1432 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/houston-aod.json @@ -0,0 +1,96 @@ +{ + "id": "houston-aod", + "type": "Collection", + "title": "Aerosol Optical Depth (AOD)", + "links": [], + "description": "The average Aerosol Optical Depth in our atmosphere. Note that these are unitless values. \n\n ### Technical Details \n\n The MCD19A2 product represents a dataset that offers insights into aerosol optical thickness over land surfaces, grounded in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. Originating from both the Terra and Aqua MODIS satellites, this dataset is remarkable for its fusion of information from multiple satellite platforms. Generated daily, the data has a high spatial resolution of 1 km per pixel, allowing detailed observiations.", + "extent": { + "spatial": { + "bbox": [ + [ + -97.00008437922591, + 27.992675617599986, + -93.99971133026672, + 31.009709499642028 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2019-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rdylbu_r", + "rescale": [ + [ + 0.1, + 0.311 + ] + ], + "nodata": 0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Nick van den Berg](https://unsplash.com/photos/2vb-_3t6YCM) (Smog Located In City)", + "href": "https://thumbnails.openveda.cloud/smog-city.png", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/houston-landcover.json b/ingestion-data/production/collections_new_metadata/houston-landcover.json new file mode 100644 index 0000000..4210736 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/houston-landcover.json @@ -0,0 +1,122 @@ +{ + "id": "houston-landcover", + "type": "Collection", + "title": "Houston Land Cover", + "links": [], + "description": "Land Use-Land Cover (LULC) is a product derived from Landsat NLCD (national Land Cover Database) data, who’s most recent iteration is from 2019 satellite imagery. \n\n ### Technical Details \n\n Terra MODIS has been instrumental in capturing LST data. This platform, orbiting Earth, scans our planet in multiple spectral bands, allowing for a detailed analysis of LST values. The data periods 2000-20009 and 2010-2019 form this satellite have been particularly enlightening, revealing distinct shifts in Houston’s urban heat profile.", + "extent": { + "spatial": { + "bbox": [ + [ + -95.99531873393823, + 29.07716802830657, + -94.29534689027045, + 30.39936449861516 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2001-01-01T00:00:00Z", + "2019-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap": { + "11": "#486DA2", + "12": "#E7EFFC", + "21": "#E1CDCE", + "22": "#DC9881", + "23": "#F10100", + "24": "#AB0101", + "31": "#B3AFA4", + "41": "#6BA966", + "42": "#1D6533", + "43": "#BDCC93", + "51": "#B29C46", + "52": "#D1BB82", + "71": "#EDECCD", + "72": "#D0D181", + "73": "#A4CC51", + "74": "#82BA9D", + "81": "#DDD83E", + "82": "#AE7229", + "90": "#BBD7ED", + "95": "#71A4C1", + "0": "#00BFFF" + }, + "nodata": -999, + "rescale": [ + [ + 0, + 255 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Arto Marttinen](https://unsplash.com/photos/6xh7H5tWj9c) (Sunset over Tokyo)", + "href": "https://thumbnails.openveda.cloud/urban-heat.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/houston-lst-day.json b/ingestion-data/production/collections_new_metadata/houston-lst-day.json new file mode 100644 index 0000000..c24021e --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/houston-lst-day.json @@ -0,0 +1,99 @@ +{ + "id": "houston-lst-day", + "type": "Collection", + "title": "Houston land surface temperature during daytime - decadal average", + "links": [], + "description": "The Land Surface Temperature (LST) data is MODIS-derived daily data, measured at 1 km spatial resolution. \n\n ### Technical Details \n\n Terra MODIS has been instrumental in capturing LST data. This platform, orbiting Earth, scans our planet in multiple spectral bands, allowing for a detailed analysis of LST values. The data periods 2000-20009 and 2010-2019 form this satellite have been particularly enlightening, revealing distinct shifts in Houston’s urban heat profile.", + "extent": { + "spatial": { + "bbox": [ + [ + -97.00008437922591, + 27.992675617599986, + -93.99971133026672, + 31.009709499642028 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2019-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "jet", + "rescale": [ + [ + 14600, + 15300 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Arto Marttinen](https://unsplash.com/photos/6xh7H5tWj9c) (Sunset over Tokyo)", + "href": "https://thumbnails.openveda.cloud/urban-heat.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/houston-lst-diff.json b/ingestion-data/production/collections_new_metadata/houston-lst-diff.json new file mode 100644 index 0000000..297f0a7 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/houston-lst-diff.json @@ -0,0 +1,99 @@ +{ + "id": "houston-lst-diff", + "type": "Collection", + "title": "Houston LST (Diff)", + "links": [], + "description": "Changes in decadally averaged land surface temperature (LST, daytime) in the Houston metro area. The higher the value, the larger the increase. \n\n ### Technical Details \n\n Terra MODIS has been instrumental in capturing LST data. This platform, orbiting Earth, scans our planet in multiple spectral bands, allowing for a detailed analysis of LST values. The data periods 2000-20009 and 2010-2019 form this satellite have been particularly enlightening, revealing distinct shifts in Houston’s urban heat profile.", + "extent": { + "spatial": { + "bbox": [ + [ + -97.00008437922591, + 27.992675617599986, + -93.99971133026672, + 31.009709499642028 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2019-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "rdbu_r", + "rescale": [ + [ + -215, + 215 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Arto Marttinen](https://unsplash.com/photos/6xh7H5tWj9c) (Sunset over Tokyo)", + "href": "https://thumbnails.openveda.cloud/urban-heat.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/houston-lst-night.json b/ingestion-data/production/collections_new_metadata/houston-lst-night.json new file mode 100644 index 0000000..a5d5ffe --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/houston-lst-night.json @@ -0,0 +1,99 @@ +{ + "id": "houston-lst-night", + "type": "Collection", + "title": "Houston land surface temperature at night time - decadal average", + "links": [], + "description": "The Land Surface Temperature (LST) data is MODIS-derived daily data, measured at 1 km spatial resolution. \n\n ### Technical Details \n\n Terra MODIS has been instrumental in capturing LST data. This platform, orbiting Earth, scans our planet in multiple spectral bands, allowing for a detailed analysis of LST values. The data periods 2000-20009 and 2010-2019 form this satellite have been particularly enlightening, revealing distinct shifts in Houston’s urban heat profile.", + "extent": { + "spatial": { + "bbox": [ + [ + -97.00008437922591, + 27.992675617599986, + -93.99971133026672, + 31.009709499642028 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2019-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "jet", + "rescale": [ + [ + 14300, + 14830 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Arto Marttinen](https://unsplash.com/photos/6xh7H5tWj9c) (Sunset over Tokyo)", + "href": "https://thumbnails.openveda.cloud/urban-heat.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/houston-ndvi.json b/ingestion-data/production/collections_new_metadata/houston-ndvi.json new file mode 100644 index 0000000..635e670 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/houston-ndvi.json @@ -0,0 +1,99 @@ +{ + "id": "houston-ndvi", + "type": "Collection", + "title": "Houston NDVI: decadal average", + "links": [], + "description": "The Normalized Difference Vegetation Index (NDVI) is a calculation of vegetative cover and health \n\n ### Technical Details \n\n Terra MODIS has been instrumental in capturing LST data. This platform, orbiting Earth, scans our planet in multiple spectral bands, allowing for a detailed analysis of LST values. The data periods 2000-20009 and 2010-2019 form this satellite have been particularly enlightening, revealing distinct shifts in Houston’s urban heat profile.", + "extent": { + "spatial": { + "bbox": [ + [ + -97.00008437922591, + 27.998655855706485, + -93.99971133026672, + 31.009709499642028 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2019-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "ylgn", + "rescale": [ + [ + -2000, + 8500 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Arto Marttinen](https://unsplash.com/photos/6xh7H5tWj9c) (Sunset over Tokyo)", + "href": "https://thumbnails.openveda.cloud/urban-heat.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/houston-urbanization.json b/ingestion-data/production/collections_new_metadata/houston-urbanization.json new file mode 100644 index 0000000..4263e9d --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/houston-urbanization.json @@ -0,0 +1,96 @@ +{ + "id": "houston-urbanization", + "type": "Collection", + "title": "New Urbanization from 2001-2019 (NLCD)", + "links": [], + "description": "This dataset illustrates the growth in the metropolitan area of Houston, TX from 2000-2019. Note that these values are from 0 to 1. \n\n ### Technical Details \n\n The National Land Cover Database (NLCD) stands as a paramount dataset offering an in-depth overview of the land cover characteristics in the United States. Spearheaded by the Earth Resources Observation and Science (EROS) Center, this database is renewed every two to three years to provide updated and accurate data for the nation.", + "extent": { + "spatial": { + "bbox": [ + [ + -97.00026404228275, + 27.999851863091195, + -93.99998082485196, + 31.008781007332363 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2001-01-01T00:00:00Z", + "2019-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "reds", + "nodata": 0, + "rescale": [ + [ + 0, + 1 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "processor" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Nick van den Berg](https://unsplash.com/photos/2vb-_3t6YCM) (Smog Located In City)", + "href": "https://thumbnails.openveda.cloud/smog-city.png", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/landfill-emit.json b/ingestion-data/production/collections_new_metadata/landfill-emit.json new file mode 100644 index 0000000..445a525 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/landfill-emit.json @@ -0,0 +1,97 @@ +{ + "id": "landfill-emit", + "type": "Collection", + "links": [], + "title": "EMIT Landfill Plumes", + "extent": { + "spatial": { + "bbox": [ + [ + -121.19141340990029, + 32.521156113298424, + -96.67328554146772, + 37.883293506113645 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2023-06-22T00:00:00+00:00", + "2023-08-25T00:00:00+00:00" + ] + ] + } + }, + "license": "CC0-1.0", + "renders": { + "dashboard": { + "bidx": [ + 1 + ], + "title": "VEDA Dashboard Render Parameters", + "assets": [ + "cog_default" + ], + "rescale": [ + [ + 1, + 1500 + ] + ], + "colormap_name": "plasma" + } + }, + "summaries": { + "datetime": [ + "2023-06-22T00:00:00Z", + "2023-08-25T00:00:00Z" + ] + }, + "description": "EMIT Methane (CH4) plumes in ppm m \n\n ### Technical Details \n\n - **Temporal Extent:** June 22, and August 25, 2023 - **Temporal Resolution:** Variable (based on ISS orbit, solar illumination, and target mask) - **Spatial Extent:** Stockton, CA and Dallas, TX - **Spatial Resolution:** 60 m - **Data Units:** Parts per million-meter (ppm m) - **Data Type:** Research", + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "stac_version": "1.0.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "dashboard:is_periodic": false, + "dashboard:time_density": "day", + "providers": [ + { + "name": "NASA", + "url": "https://nasa.gov", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Nick van den Berg](https://unsplash.com/photos/2vb-_3t6YCM) (Smog Located In City)", + "href": "https://thumbnails.openveda.cloud/smog-city.png", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/landsat-nighttime-thermal.json b/ingestion-data/production/collections_new_metadata/landsat-nighttime-thermal.json new file mode 100644 index 0000000..2f1f81c --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/landsat-nighttime-thermal.json @@ -0,0 +1,79 @@ +{ + "id": "landsat-nighttime-thermal", + "type": "Collection", + "title": "Landsat 8 Nighttime Thermal Imagery", + "links": [], + "description": "Nighttime Thermal band from Landsat-8 on August 8, 2023 shows the extent of the ongoing Lahaina Fire. \n\n ### Technical Details \n\n On August 8th, 2023, a devastating wildfire rapidly spread through the city of Lahaina, Hawai’i, which is located on the island of Maui and home to over 13,000 residents. This destructive wildfire was initially ignited by a downed powerline on Lahainaluna Road and was later fueled by intense wind gusts that persisted throughout the day. The National Weather Service recorded wind gusts as high as 67 mph in the area, contributing to the rapid spread of the wildfire across much of Lahaina during the afternoon hours of August 8th.", + "extent": { + "spatial": { + "bbox": [ + [ + -156.6965307041471, + 20.842180322849387, + -156.64330803549817, + 20.911686593495485 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2023-08-08T00:00:00Z", + "2023-08-08T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "providers": [ + { + "name": "USGS", + "url": "https://lpdaac.usgs.gov/product_search/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Matthew Thayer/AP](https://www.sfchronicle.com/travel/article/hawaii-fire-maui-lahaina-18289213.php) (Wildfire erupting over Lahaina, HI, August 8, 2023)", + "href": "https://thumbnails.openveda.cloud/lahaina-fire-background.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-etsuppression.json b/ingestion-data/production/collections_new_metadata/lis-etsuppression.json new file mode 100644 index 0000000..d8a7d79 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-etsuppression.json @@ -0,0 +1,89 @@ +{ + "id": "lis-etsuppression", + "type": "Collection", + "title": "Change in ET for 2020 fires using LIS outputs", + "links": [], + "description": "ET anomaly for 2020 fires using model outputs from Land Information System (LIS) framework that synthesizes multiple remote sensing observations within the Noah-MP land surface model. \n\n ### Technical Details \n\n Change in ET for 2020 fires using model outputs from Land Information System (LIS) framework that synthesizes multiple remote sensing observations within the Noah-MP land surface model. Change is calculated as the difference of ET in the immediate post-fire water year from that in the immediate pre-fire water year. The difference is normalized by pre-fire ET and negative values denote vegetation disturbance induced by fire or by a climatological anomaly resulting in the decline in ET.", + "extent": { + "spatial": { + "bbox": [ + [ + -125.03991200973752, + 31.972665113477177, + -109.401550219135, + 49.27566382776904 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2020-01-01T00:00:00Z", + "2020-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "asset_bidx": "cog_default|1", + "colormap_name": "rdylbu", + "rescale": [ + [ + -0.6, + 0.6 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mike Newbry](https://unsplash.com/photos/DwtX9mMHBJ0) (Hillside engulfed by wildfire)", + "href": "https://thumbnails.openveda.cloud/mtbs-burn-severity--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-global-da-evap.json b/ingestion-data/production/collections_new_metadata/lis-global-da-evap.json new file mode 100644 index 0000000..9074868 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-global-da-evap.json @@ -0,0 +1,92 @@ +{ + "id": "lis-global-da-evap", + "type": "Collection", + "title": "Evapotranspiration - LIS 10km Global DA", + "links": [], + "description": "Gridded total evapotranspiration (in kg m-2 s-1) from 10km global LIS with assimilation \n\n ### Technical Details \n\n The reanalysis product is created using the [NASA Land Information System](https://lis.gsfc.nasa.gov/) modeling framework to merge land surface model simulations with observations from satellites through data assimilation. The team uses the Noah-MP land surface model and assimilates soil moisture from the European Space Agency’s Climate Change Initiative Program (ESA CCI), leaf area index from the Moderate Resolution Imaging Spectroradiometer (MODIS), and terrestrial water storage anomalies from the Gravity Recovery and Climate Experiment and the follow-on missions (GRACE/GRACE-FO).", + "extent": { + "spatial": { + "bbox": [ + [ + -179.9500000157243, + -59.98224871364589, + 179.9973980503783, + 89.9999999874719 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2002-08-02T00:00:00Z", + "2021-12-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "viridis", + "rescale": [ + [ + 0, + 0.0001 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (One day of terrestrial water storage from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/global_tws_blackbg_v2.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-global-da-gpp-trend.json b/ingestion-data/production/collections_new_metadata/lis-global-da-gpp-trend.json new file mode 100644 index 0000000..baefb94 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-global-da-gpp-trend.json @@ -0,0 +1,92 @@ +{ + "id": "lis-global-da-gpp-trend", + "type": "Collection", + "title": "Gross Primary Productivity Trend - LIS 10km Global DA", + "links": [], + "description": "Trends in GPP from LIS data assimilation output \n\n ### Technical Details \n\n Realistic estimates of water and energy cycle variables are necessary for accurate understanding of earth system processes. We develop a 10 km global reanalysis product of water, energy, and carbon fluxes by assimilating satellite observed surface soil moisture, leaf area index, and terrestrial water storage anomalies into a land surface model within NASA Land Information System Framework. We applied a seasonal and trend decomposition algorithm to get the trend estimates for terrestrial water storage and gross primary production. The method can better help to deal with [nonstationarities](https://github.com/Earth-Information-System/sea-level-and-coastal-risk/blob/main/AMS_2023_Wanshu_Nie_for_VEDA_Discovery.pdf) and seasonal shifts and provide a more robust estimate of trends.", + "extent": { + "spatial": { + "bbox": [ + [ + -179.9500000157243, + -59.98224871364589, + 179.9973980503783, + 89.9999999874719 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2003-01-01T00:00:00Z", + "2021-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "bidx": [ + 1 + ], + "colormap_name": "rdbu", + "rescale": [ + [ + -40, + 40 + ] + ], + "nodata": -9999.0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (TWS trend of anomalies from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/twsanomaly-globe.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-global-da-gpp.json b/ingestion-data/production/collections_new_metadata/lis-global-da-gpp.json new file mode 100644 index 0000000..4ff29c1 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-global-da-gpp.json @@ -0,0 +1,92 @@ +{ + "id": "lis-global-da-gpp", + "type": "Collection", + "title": "Gross Primary Productivity - LIS 10km Global DA", + "links": [], + "description": "Gridded gross primary productivity (in g m-2 s-1) from 10km global LIS with assimilation \n\n ### Technical Details \n\n The reanalysis product is created using the [NASA Land Information System](https://lis.gsfc.nasa.gov/) modeling framework to merge land surface model simulations with observations from satellites through data assimilation. The team uses the Noah-MP land surface model and assimilates soil moisture from the European Space Agency’s Climate Change Initiative Program (ESA CCI), leaf area index from the Moderate Resolution Imaging Spectroradiometer (MODIS), and terrestrial water storage anomalies from the Gravity Recovery and Climate Experiment and the follow-on missions (GRACE/GRACE-FO).", + "extent": { + "spatial": { + "bbox": [ + [ + -179.9500000157243, + -59.98224871364589, + 179.9973980503783, + 89.9999999874719 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2002-08-02T00:00:00Z", + "2021-12-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "viridis", + "rescale": [ + [ + 0, + 0.0001 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (One day of terrestrial water storage from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/global_tws_blackbg_v2.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-global-da-gws.json b/ingestion-data/production/collections_new_metadata/lis-global-da-gws.json new file mode 100644 index 0000000..17e4e55 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-global-da-gws.json @@ -0,0 +1,92 @@ +{ + "id": "lis-global-da-gws", + "type": "Collection", + "title": "Groundwater Storage - LIS 10km Global DA", + "links": [], + "description": "Gridded groundwater storage (in mm) from 10km global LIS with assimilation \n\n ### Technical Details \n\n The reanalysis product is created using the [NASA Land Information System](https://lis.gsfc.nasa.gov/) modeling framework to merge land surface model simulations with observations from satellites through data assimilation. The team uses the Noah-MP land surface model and assimilates soil moisture from the European Space Agency’s Climate Change Initiative Program (ESA CCI), leaf area index from the Moderate Resolution Imaging Spectroradiometer (MODIS), and terrestrial water storage anomalies from the Gravity Recovery and Climate Experiment and the follow-on missions (GRACE/GRACE-FO).", + "extent": { + "spatial": { + "bbox": [ + [ + -179.9500000157243, + -59.98224871364589, + 179.9973980503783, + 89.9999999874719 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2002-08-02T00:00:00Z", + "2021-12-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "viridis", + "rescale": [ + [ + 4500, + 5000 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (One day of terrestrial water storage from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/global_tws_blackbg_v2.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-global-da-qs.json b/ingestion-data/production/collections_new_metadata/lis-global-da-qs.json new file mode 100644 index 0000000..2463544 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-global-da-qs.json @@ -0,0 +1,92 @@ +{ + "id": "lis-global-da-qs", + "type": "Collection", + "title": "Surface runoff - LIS 10km Global DA", + "links": [], + "description": "Gridded surface runoff (in kg m-2 s-1) from 10km global LIS with assimilation \n\n ### Technical Details \n\n The reanalysis product is created using the [NASA Land Information System](https://lis.gsfc.nasa.gov/) modeling framework to merge land surface model simulations with observations from satellites through data assimilation. The team uses the Noah-MP land surface model and assimilates soil moisture from the European Space Agency’s Climate Change Initiative Program (ESA CCI), leaf area index from the Moderate Resolution Imaging Spectroradiometer (MODIS), and terrestrial water storage anomalies from the Gravity Recovery and Climate Experiment and the follow-on missions (GRACE/GRACE-FO).", + "extent": { + "spatial": { + "bbox": [ + [ + -179.9500000157243, + -59.98224871364589, + 179.9973980503783, + 89.9999999874719 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2002-08-02T00:00:00Z", + "2021-12-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "viridis", + "rescale": [ + [ + 0, + 0.0001 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (One day of terrestrial water storage from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/global_tws_blackbg_v2.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-global-da-qsb.json b/ingestion-data/production/collections_new_metadata/lis-global-da-qsb.json new file mode 100644 index 0000000..d551f28 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-global-da-qsb.json @@ -0,0 +1,92 @@ +{ + "id": "lis-global-da-qsb", + "type": "Collection", + "title": "Subsurface Runoff - LIS 10km Global DA", + "links": [], + "description": "Gridded subsurface runoff (in kg m-2 s-1) from 10km global LIS with assimilation \n\n ### Technical Details \n\n The reanalysis product is created using the [NASA Land Information System](https://lis.gsfc.nasa.gov/) modeling framework to merge land surface model simulations with observations from satellites through data assimilation. The team uses the Noah-MP land surface model and assimilates soil moisture from the European Space Agency’s Climate Change Initiative Program (ESA CCI), leaf area index from the Moderate Resolution Imaging Spectroradiometer (MODIS), and terrestrial water storage anomalies from the Gravity Recovery and Climate Experiment and the follow-on missions (GRACE/GRACE-FO).", + "extent": { + "spatial": { + "bbox": [ + [ + -179.9500000157243, + -59.98224871364589, + 179.9973980503783, + 89.9999999874719 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2002-08-02T00:00:00Z", + "2021-12-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "viridis", + "rescale": [ + [ + 0, + 0.0001 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (One day of terrestrial water storage from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/global_tws_blackbg_v2.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-global-da-streamflow.json b/ingestion-data/production/collections_new_metadata/lis-global-da-streamflow.json new file mode 100644 index 0000000..08e828d --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-global-da-streamflow.json @@ -0,0 +1,92 @@ +{ + "id": "lis-global-da-streamflow", + "type": "Collection", + "title": "Streamflow - LIS 10km Global DA", + "links": [], + "description": "Routed streamflow (in m3 s-1) from 10km global LIS+HyMAP with assimilation \n\n ### Technical Details \n\n The reanalysis product is created using the [NASA Land Information System](https://lis.gsfc.nasa.gov/) modeling framework to merge land surface model simulations with observations from satellites through data assimilation. The team uses the Noah-MP land surface model and assimilates soil moisture from the European Space Agency’s Climate Change Initiative Program (ESA CCI), leaf area index from the Moderate Resolution Imaging Spectroradiometer (MODIS), and terrestrial water storage anomalies from the Gravity Recovery and Climate Experiment and the follow-on missions (GRACE/GRACE-FO).", + "extent": { + "spatial": { + "bbox": [ + [ + -179.9500000157243, + -59.98224871364589, + 179.9973980503783, + 89.9999999874719 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2002-08-01T00:00:00Z", + "2019-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "viridis", + "rescale": [ + [ + 0, + 2500 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (One day of terrestrial water storage from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/global_tws_blackbg_v2.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-global-da-swe.json b/ingestion-data/production/collections_new_metadata/lis-global-da-swe.json new file mode 100644 index 0000000..b2ef168 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-global-da-swe.json @@ -0,0 +1,92 @@ +{ + "id": "lis-global-da-swe", + "type": "Collection", + "title": "Snow Water Equivalent - LIS 10km Global DA", + "links": [], + "description": "Gridded snow water equivalent (in kg m-2) from 10km global LIS with assimilation \n\n ### Technical Details \n\n The reanalysis product is created using the [NASA Land Information System](https://lis.gsfc.nasa.gov/) modeling framework to merge land surface model simulations with observations from satellites through data assimilation. The team uses the Noah-MP land surface model and assimilates soil moisture from the European Space Agency’s Climate Change Initiative Program (ESA CCI), leaf area index from the Moderate Resolution Imaging Spectroradiometer (MODIS), and terrestrial water storage anomalies from the Gravity Recovery and Climate Experiment and the follow-on missions (GRACE/GRACE-FO).", + "extent": { + "spatial": { + "bbox": [ + [ + -179.9500000157243, + -59.98224871364589, + 179.9973980503783, + 89.9999999874719 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2002-08-02T00:00:00Z", + "2021-12-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "blues", + "rescale": [ + [ + 0, + 500 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (One day of terrestrial water storage from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/global_tws_blackbg_v2.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-global-da-totalprecip.json b/ingestion-data/production/collections_new_metadata/lis-global-da-totalprecip.json new file mode 100644 index 0000000..df72274 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-global-da-totalprecip.json @@ -0,0 +1,92 @@ +{ + "id": "lis-global-da-totalprecip", + "type": "Collection", + "title": "Total Precipitation - LIS 10km Global DA", + "links": [], + "description": "Gridded total precipitation (in kg m-2 s-1) from 10km global LIS with assimilation \n\n ### Technical Details \n\n The reanalysis product is created using the [NASA Land Information System](https://lis.gsfc.nasa.gov/) modeling framework to merge land surface model simulations with observations from satellites through data assimilation. The team uses the Noah-MP land surface model and assimilates soil moisture from the European Space Agency’s Climate Change Initiative Program (ESA CCI), leaf area index from the Moderate Resolution Imaging Spectroradiometer (MODIS), and terrestrial water storage anomalies from the Gravity Recovery and Climate Experiment and the follow-on missions (GRACE/GRACE-FO).", + "extent": { + "spatial": { + "bbox": [ + [ + -179.9500000157243, + -59.98224871364589, + 179.9973980503783, + 89.9999999874719 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2002-01-02T00:00:00Z", + "2022-03-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "blues", + "rescale": [ + [ + 0, + 0.0001 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (One day of terrestrial water storage from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/global_tws_blackbg_v2.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-global-da-tws-trend.json b/ingestion-data/production/collections_new_metadata/lis-global-da-tws-trend.json new file mode 100644 index 0000000..572170e --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-global-da-tws-trend.json @@ -0,0 +1,92 @@ +{ + "id": "lis-global-da-tws-trend", + "type": "Collection", + "title": "Terrestrial Water Storage Trend - LIS 10km Global DA", + "links": [], + "description": "Trends in TWS from LIS data assimilation output \n\n ### Technical Details \n\n Realistic estimates of water and energy cycle variables are necessary for accurate understanding of earth system processes. We develop a 10 km global reanalysis product of water, energy, and carbon fluxes by assimilating satellite observed surface soil moisture, leaf area index, and terrestrial water storage anomalies into a land surface model within NASA Land Information System Framework. We applied a seasonal and trend decomposition algorithm to get the trend estimates for terrestrial water storage and gross primary production. The method can better help to deal with [nonstationarities](https://github.com/Earth-Information-System/sea-level-and-coastal-risk/blob/main/AMS_2023_Wanshu_Nie_for_VEDA_Discovery.pdf) and seasonal shifts and provide a more robust estimate of trends.", + "extent": { + "spatial": { + "bbox": [ + [ + -179.9500000157243, + -59.98224871364589, + 179.9973980503783, + 89.9999999874719 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2003-01-01T00:00:00Z", + "2021-12-31T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "bidx": [ + 1 + ], + "colormap_name": "rdbu", + "rescale": [ + [ + -20, + 20 + ] + ], + "nodata": -9999.0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (TWS trend of anomalies from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/twsanomaly-globe.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-global-da-tws.json b/ingestion-data/production/collections_new_metadata/lis-global-da-tws.json new file mode 100644 index 0000000..42be424 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-global-da-tws.json @@ -0,0 +1,92 @@ +{ + "id": "lis-global-da-tws", + "type": "Collection", + "title": "Terrestrial Water Storage - LIS 10km Global DA", + "links": [], + "description": "Gridded terrestrial water storage (in mm) from 10km global LIS with assimilation \n\n ### Technical Details \n\n The reanalysis product is created using the [NASA Land Information System](https://lis.gsfc.nasa.gov/) modeling framework to merge land surface model simulations with observations from satellites through data assimilation. The team uses the Noah-MP land surface model and assimilates soil moisture from the European Space Agency’s Climate Change Initiative Program (ESA CCI), leaf area index from the Moderate Resolution Imaging Spectroradiometer (MODIS), and terrestrial water storage anomalies from the Gravity Recovery and Climate Experiment and the follow-on missions (GRACE/GRACE-FO).", + "extent": { + "spatial": { + "bbox": [ + [ + -179.9500000157243, + -59.98224871364589, + 179.9973980503783, + 89.9999999874719 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2002-08-02T00:00:00Z", + "2021-12-01T23:59:59Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "viridis", + "rescale": [ + [ + 5000, + 5800 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (One day of terrestrial water storage from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/global_tws_blackbg_v2.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-tvegsuppression.json b/ingestion-data/production/collections_new_metadata/lis-tvegsuppression.json new file mode 100644 index 0000000..87daadf --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-tvegsuppression.json @@ -0,0 +1,89 @@ +{ + "id": "lis-tvegsuppression", + "type": "Collection", + "title": "Change in transpiration for 2020 fires using LIS outputs", + "links": [], + "description": "Standardized transpiration anomalies for 2020 fires using model outputs from Land Information System (LIS) framework that synthesizes multiple remote sensing observations within the Noah-MP land surface model. \n\n ### Technical Details \n\n Change in vegetation transpiration for 2020 fires using model outputs from Land Information System (LIS) framework that synthesizes multiple remote sensing observations within the Noah-MP land surface model. Change is calculated as the difference of transpiration in the immediate post-fire water year from that in the immediate pre-fire water year. The difference is normalized by pre-fire transpiration and negative values denote vegetation disturbance induced by fire or by a climatological anomaly resulting in the decline in transpiration.", + "extent": { + "spatial": { + "bbox": [ + [ + -125.03991200973752, + 31.972665113477177, + -109.401550219135, + 49.27566382776904 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2020-01-01T00:00:00Z", + "2020-12-31T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "asset_bidx": "cog_default|1", + "colormap_name": "rdylbu", + "rescale": [ + [ + -0.6, + 0.6 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mike Newbry](https://unsplash.com/photos/DwtX9mMHBJ0) (Hillside engulfed by wildfire)", + "href": "https://thumbnails.openveda.cloud/mtbs-burn-severity--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-tws-anomaly.json b/ingestion-data/production/collections_new_metadata/lis-tws-anomaly.json new file mode 100644 index 0000000..c9fb308 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-tws-anomaly.json @@ -0,0 +1,92 @@ +{ + "id": "lis-tws-anomaly", + "type": "Collection", + "title": "Terrestrial Water Storage (TWS) Anomalies", + "links": [], + "description": "TWS anomalies modeled using data assimilation within Land Information System framework \n\n ### Technical Details \n\n Terrestrial water storage (TWS) is defined as the summation of all water on the land surface and in the subsurface. It includes surface soil moisture, root zone soil moisture, groundwater, snow, ice, water stored in the vegetation, river and lake water.", + "extent": { + "spatial": { + "bbox": [ + [ + -179.9500000157243, + -59.98224871364589, + 179.9973980503783, + 89.9999999874719 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2002-09-01T00:00:00Z", + "2021-12-01T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "rdylbu", + "rescale": [ + [ + -200, + 200 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (TWS trend of anomalies from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/twsanomaly-globe.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-tws-nonstationarity-index.json b/ingestion-data/production/collections_new_metadata/lis-tws-nonstationarity-index.json new file mode 100644 index 0000000..3f0af09 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-tws-nonstationarity-index.json @@ -0,0 +1,92 @@ +{ + "id": "lis-tws-nonstationarity-index", + "type": "Collection", + "title": "Global TWS Non-Stationarity Index", + "links": [], + "description": "TWS Non-Stationarity Index \n\n ### Technical Details \n\n Terrestrial water storage (TWS) is defined as the summation of all water on the land surface and in the subsurface. It includes surface soil moisture, root zone soil moisture, groundwater, snow, ice, water stored in the vegetation, river and lake water.", + "extent": { + "spatial": { + "bbox": [ + [ + -179.95, + -59.95, + 179.95, + 89.95 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2003-01-01T00:00:00Z", + "2020-01-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "bidx": [ + 1 + ], + "colormap_name": "rdylbu", + "rescale": [ + [ + -1, + 1 + ] + ], + "nodata": -9999, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (TWS trend of anomalies from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/twsanomaly-globe.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/lis-tws-trend.json b/ingestion-data/production/collections_new_metadata/lis-tws-trend.json new file mode 100644 index 0000000..22ec5fd --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/lis-tws-trend.json @@ -0,0 +1,92 @@ +{ + "id": "lis-tws-trend", + "type": "Collection", + "title": "Trend in Terrestrial Water Storage (TWS) Anomalies", + "links": [], + "description": "Trends in TWS anomalies from LIS outputs \n\n ### Technical Details \n\n Terrestrial water storage (TWS) is defined as the summation of all water on the land surface and in the subsurface. It includes surface soil moisture, root zone soil moisture, groundwater, snow, ice, water stored in the vegetation, river and lake water.", + "extent": { + "spatial": { + "bbox": [ + [ + -179.95000001572427, + -59.98224871364587, + 179.99739805037828, + 89.99999998747188 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2001-01-01T00:00:00Z", + "2021-12-31T23:59:59Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "bidx": [ + 1 + ], + "colormap_name": "rdylbu", + "rescale": [ + [ + -1, + 1 + ] + ], + "nodata": -9999, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Land Information System (LIS)", + "url": "https://lis.gsfc.nasa.gov/", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by NASA LIS (TWS trend of anomalies from LIS outputs)", + "href": "https://thumbnails.openveda.cloud/twsanomaly-globe.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/mtbs-burn-severity.json b/ingestion-data/production/collections_new_metadata/mtbs-burn-severity.json new file mode 100644 index 0000000..e2510c3 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/mtbs-burn-severity.json @@ -0,0 +1,91 @@ +{ + "id": "mtbs-burn-severity", + "type": "Collection", + "title": "MTBS Burn Severity", + "links": [], + "description": "Burn severities and extents of fires from Monitoring Trends in Burn Severity (MTBS) program during the years 2016-2021 over Western US \n\n ### Technical Details \n\n Change in vegetation transpiration for 2020 fires using model outputs from Land Information System (LIS) framework that synthesizes multiple remote sensing observations within the Noah-MP land surface model. Change is calculated as the difference of transpiration in the immediate post-fire water year from that in the immediate pre-fire water year. The difference is normalized by pre-fire transpiration and negative values denote vegetation disturbance induced by fire or by a climatological anomaly resulting in the decline in transpiration.", + "extent": { + "spatial": { + "bbox": [ + [ + -127.1623805772434, + 23.821031278155107, + -71.13506805308776, + 49.08850271850093 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2016-01-01T00:00:00Z", + "2020-12-31T23:59:59Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "rdylgn_r", + "rescale": [ + [ + 1, + 4 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "Monitoring Trends in Burn Severity", + "url": "https://www.mtbs.gov/", + "roles": [ + "producer", + "processor", + "licensor", + "host" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mike Newbry](https://unsplash.com/photos/DwtX9mMHBJ0) (Hillside engulfed by wildfire)", + "href": "https://thumbnails.openveda.cloud/mtbs-burn-severity--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/nceo_africa_2017.json b/ingestion-data/production/collections_new_metadata/nceo_africa_2017.json new file mode 100644 index 0000000..bdba5b9 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/nceo_africa_2017.json @@ -0,0 +1,97 @@ +{ + "id": "nceo_africa_2017", + "type": "Collection", + "title": "NCEO Africa Aboveground Woody Biomass 2017", + "links": [ + { + "rel": "external", + "href": "https://ceos.org/gst/africa-biomass.html", + "type": "text/html", + "title": "NCEO Africa Aboveground Woody Biomass 2017 (CEOS Website)" + } + ], + "description": "The NCEO Africa Aboveground Woody Biomass (AGB) map for the year 2017 at 100 m spatial resolution \n\n ### Technical Details \n\n The NCEO Africa Aboveground Woody Biomass (AGB) map for the year 2017 at 100 m spatial resolution was developed using a combination of LiDAR, Synthetic Aperture Radar (SAR) and optical based data. This product was developed by the UK’s National Centre for Earth Observation (NCEO) through the Carbon Cycle and Official Development Assistance (ODA) programmes. For more information see [CEOS biomass](https://ceos.org/gst/biomass.html).", + "extent": { + "spatial": { + "bbox": [ + [ + -18.273529509559307, + -35.054059016911935, + 51.86423292864056, + 37.73103856358817 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-01-01T00:00:00Z", + "2017-12-31T23:59:59Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "colormap_name": "gist_earth_r", + "rescale": [ + [ + 0, + 400 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "National Center for Earth Observation", + "url": "https://ceos.org/gst/africa-biomass.html", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Olena Sergienko](https://unsplash.com/photos/0Ws_-v4Y_wY) (Green trees seen from above)", + "href": "https://thumbnails.openveda.cloud/nceo-africa--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/nightlights-hd-1band.json b/ingestion-data/production/collections_new_metadata/nightlights-hd-1band.json new file mode 100644 index 0000000..52a55f7 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/nightlights-hd-1band.json @@ -0,0 +1,99 @@ +{ + "id": "nightlights-hd-1band", + "type": "Collection", + "title": "Black Marble High Definition Nightlights 1 band Dataset", + "links": [], + "description": "High definition nighttime lights can be used to identify regions impacted by natural disaster and/or power outages to better inform disaster response efforts. \n\n ### Technical Details \n\n Nightlights data are collected by the [Visible Infrared Radiometer Suite (VIIRS) Day/Night Band (DNB)](https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/viirs/) on the Suomi-National Polar-Orbiting Partnership (Suomi-NPP) platform, a joint National Oceanic and Atmospheric Administration (NOAA) and NASA satellite. The images are produced by [NASA’s Black Marble](https://blackmarble.gsfc.nasa.gov/) products suite. All data are calibrated daily, corrected, and validated with ground measurements for science-ready analysis.", + "extent": { + "spatial": { + "bbox": [ + [ + -90.3037818244749, + 17.912138994450856, + -65.57478762584185, + 30.07177072705947 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-07-21T00:00:00Z", + "2021-08-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "bidx": [ + 1 + ], + "colormap_name": "inferno", + "rescale": [ + [ + 0, + 255 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA", + "url": "https://blackmarble.gsfc.nasa.gov/", + "roles": [ + "producer", + "processor" + ] + }, + { + "name": "NOAA", + "url": "https://www.noaa.gov", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA Earth Observatory](https://appliedsciences.nasa.gov/our-impact/news/satellite-observes-power-outages-new-orleans) (Nighttime lights for New Orleans, LA on August 31, 2021)", + "href": "https://thumbnails.openveda.cloud/nighttime-lights-ej--dataset-cover-neworleans.jpeg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/nightlights-hd-monthly.json b/ingestion-data/production/collections_new_metadata/nightlights-hd-monthly.json new file mode 100644 index 0000000..66e9c2b --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/nightlights-hd-monthly.json @@ -0,0 +1,99 @@ +{ + "id": "nightlights-hd-monthly", + "type": "Collection", + "title": "Black Marble High Definition Nightlights Monthly Dataset", + "links": [], + "description": "Nightlights data are collected by the Visible Infrared Radiometer Suite (VIIRS) Day/Night Band (DNB) on the Suomi-National Polar-Orbiting Partnership (Suomi-NPP) platform, a joint National Oceanic and Atmospheric Administration (NOAA) and NASA satellite. \n\n ### Technical Details \n\n Nightlights data are collected by the [Visible Infrared Radiometer Suite (VIIRS) Day/Night Band (DNB)](https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/viirs/) on the Suomi-National Polar-Orbiting Partnership (Suomi-NPP) platform, a joint National Oceanic and Atmospheric Administration (NOAA) and NASA satellite. The images are produced by [NASA’s Black Marble](https://blackmarble.gsfc.nasa.gov/) products suite. All data are calibrated daily, corrected, and validated with ground measurements for science-ready analysis.", + "extent": { + "spatial": { + "bbox": [ + [ + -122.63569641113281, + -37.08, + 174.96, + 54.584515 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2019-01-01T00:00:00Z", + "2022-03-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "bidx": [ + 1 + ], + "colormap_name": "inferno", + "rescale": [ + [ + 0, + 255 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA", + "url": "https://blackmarble.gsfc.nasa.gov/", + "roles": [ + "producer", + "processor" + ] + }, + { + "name": "NOAA", + "url": "https://www.noaa.gov", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA Earth Observatory](https://earthobservatory.nasa.gov/images/90008/night-light-maps-open-up-new-applications) (Satellite image of Earth at night)", + "href": "https://thumbnails.openveda.cloud/nighttime-lights--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/no2-monthly-diff.json b/ingestion-data/production/collections_new_metadata/no2-monthly-diff.json new file mode 100644 index 0000000..a7b84ea --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/no2-monthly-diff.json @@ -0,0 +1,93 @@ +{ + "id": "no2-monthly-diff", + "type": "Collection", + "title": "NO₂ (Diff)", + "links": [], + "description": "Global nitrogen dioxide (NO₂) data which displays the difference from the same time 1 year ago \n\n ### Technical Details \n\n OMI, which launched in 2004, preceded TROPOMI, which launched in 2017. While TROPOMI provides higher resolution information, the longer OMI data record provides context for the TROPOMI observations.", + "extent": { + "spatial": { + "bbox": [ + [ + -180, + -90, + 180, + 90 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2015-01-01T00:00:00Z", + "2022-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json", + "https://stac-extensions.github.io/render/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "rdbu_r", + "rescale": [ + [ + -8000000000000000.0, + 8000000000000000.0 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Goddard Earth Sciences Data and Information Services Center", + "url": "https://disc.gsfc.nasa.gov/", + "roles": [ + "producer", + "processor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mick Truyts](https://unsplash.com/photos/x6WQeNYJC1w) (Power plant shooting steam at the sky)", + "href": "https://thumbnails.openveda.cloud/no2--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/no2-monthly.json b/ingestion-data/production/collections_new_metadata/no2-monthly.json new file mode 100644 index 0000000..91ccb1f --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/no2-monthly.json @@ -0,0 +1,94 @@ +{ + "id": "no2-monthly", + "type": "Collection", + "title": "NO₂", + "links": [], + "description": "Global nitrogen dioxide (NO₂) data organized into monthly metrics \n\n ### Technical Details \n\n OMI, which launched in 2004, preceded TROPOMI, which launched in 2017. While TROPOMI provides higher resolution information, the longer OMI data record provides context for the TROPOMI observations.", + "extent": { + "spatial": { + "bbox": [ + [ + -180, + -90, + 180, + 90 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2016-01-01T00:00:00Z", + "2022-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json", + "https://stac-extensions.github.io/render/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": true, + "dashboard:time_density": "month", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "color_formula": "gamma r 1.05", + "colormap_name": "rdbu_r", + "rescale": [ + [ + 0, + 1.5e+16 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Goddard Earth Sciences Data and Information Services Center", + "url": "https://disc.gsfc.nasa.gov/", + "roles": [ + "producer", + "processor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Mick Truyts](https://unsplash.com/photos/x6WQeNYJC1w) (Power plant shooting steam at the sky)", + "href": "https://thumbnails.openveda.cloud/no2--dataset-cover.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/snow-projections-diff-245.json b/ingestion-data/production/collections_new_metadata/snow-projections-diff-245.json new file mode 100644 index 0000000..9bbe390 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/snow-projections-diff-245.json @@ -0,0 +1,102 @@ +{ + "id": "snow-projections-diff-245", + "type": "Collection", + "title": "Projections of Snow Water Equivalent (SWE) Losses - SSP2-4.5", + "links": [], + "description": "Snow water equivalent (SWE) losses modeled using the Land Information System framework and CMIP6 SSP2-4.5 scenario projections \n\n ### Technical Details \n\n Snow water equivalent (SWE) is defined as the amount of water in the snow. Here, we present the projected percent-change to projected snow in future periods, relative to the historical period (1995 - 2014).", + "extent": { + "spatial": { + "bbox": [ + [ + -121.2149658203125, + 36.66500091552734, + -105.40498779296708, + 49.064999694823946 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-04-01T00:00:00Z", + "2077-05-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "nodata": "nan", + "colormap_name": "rdbu", + "rescale": [ + [ + -100, + 100 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Center for Climate Simulation (NCCS)", + "url": "https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-gddp-cmip6", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA Earth Information System", + "url": "https://www.earthdata.nasa.gov/eis", + "roles": [ + "processor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by Justin Pflug (Photo of Matterhorn glacier field)", + "href": "https://thumbnails.openveda.cloud/snow-projections-median.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/snow-projections-diff-585.json b/ingestion-data/production/collections_new_metadata/snow-projections-diff-585.json new file mode 100644 index 0000000..a613b66 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/snow-projections-diff-585.json @@ -0,0 +1,102 @@ +{ + "id": "snow-projections-diff-585", + "type": "Collection", + "title": "Projections of Snow Water Equivalent (SWE) Losses - SSP5-8.5", + "links": [], + "description": "Snow water equivalent (SWE) losses modeled using the Land Information System framework and CMIP SSP5-8.5 scenario projections \n\n ### Technical Details \n\n Snow water equivalent (SWE) is defined as the amount of water in the snow. Here, we present the projected percent-change to projected snow in future periods, relative to the historical period (1995 - 2014).", + "extent": { + "spatial": { + "bbox": [ + [ + -121.2149658203125, + 36.66500091552734, + -105.40498779296708, + 49.064999694823946 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-04-01T00:00:00Z", + "2077-05-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "nodata": "nan", + "colormap_name": "rdbu", + "rescale": [ + [ + -100, + 100 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Center for Climate Simulation (NCCS)", + "url": "https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-gddp-cmip6", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA Earth Information System", + "url": "https://www.earthdata.nasa.gov/eis", + "roles": [ + "processor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by Justin Pflug (Photo of Matterhorn glacier field)", + "href": "https://thumbnails.openveda.cloud/snow-projections-median.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/snow-projections-median-245.json b/ingestion-data/production/collections_new_metadata/snow-projections-median-245.json new file mode 100644 index 0000000..2ddb183 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/snow-projections-median-245.json @@ -0,0 +1,101 @@ +{ + "id": "snow-projections-median-245", + "type": "Collection", + "title": "Projections of Snow Water Equivalent (SWE) - SSP2-4.5", + "links": [], + "description": "Snow water equivalent modeled using the Land Information System framework and CMIP6 SSP2-4.5 scenario projections \n\n ### Technical Details \n\n Snow water equivalent (SWE) is defined as the amount of water in the snow. It is expressed as a height (in millimeters), representative of the height of water that would exist if snow was only in a liquid state.", + "extent": { + "spatial": { + "bbox": [ + [ + -121.2149658203125, + 36.66500091552734, + -105.40498779296708, + 49.064999694823946 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-04-01T00:00:00Z", + "2077-05-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "blues", + "rescale": [ + [ + 0, + 1000 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Center for Climate Simulation (NCCS)", + "url": "https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-gddp-cmip6", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA Earth Information System", + "url": "https://www.earthdata.nasa.gov/eis", + "roles": [ + "processor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by Justin Pflug (Photo of Matterhorn glacier field)", + "href": "https://thumbnails.openveda.cloud/snow-projections-median.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/snow-projections-median-585.json b/ingestion-data/production/collections_new_metadata/snow-projections-median-585.json new file mode 100644 index 0000000..0b65035 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/snow-projections-median-585.json @@ -0,0 +1,101 @@ +{ + "id": "snow-projections-median-585", + "type": "Collection", + "title": "Projections of Snow Water Equivalent (SWE) - SSP5-8.5", + "links": [], + "description": "Snow water equivalent modeled using the Land Information System framework and CMIP6 SSP5-8.5 scenario projections \n\n ### Technical Details \n\n Snow water equivalent (SWE) is defined as the amount of water in the snow. It is expressed as a height (in millimeters), representative of the height of water that would exist if snow was only in a liquid state.", + "extent": { + "spatial": { + "bbox": [ + [ + -121.2149658203125, + 36.66500091552734, + -105.40498779296708, + 49.064999694823946 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2017-04-01T00:00:00Z", + "2077-05-01T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": null, + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "blues", + "rescale": [ + [ + 0, + 1000 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Center for Climate Simulation (NCCS)", + "url": "https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-gddp-cmip6", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA Earth Information System", + "url": "https://www.earthdata.nasa.gov/eis", + "roles": [ + "processor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by Justin Pflug (Photo of Matterhorn glacier field)", + "href": "https://thumbnails.openveda.cloud/snow-projections-median.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/social-vulnerability-index-household-nopop.json b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-household-nopop.json new file mode 100644 index 0000000..3f3d4cd --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-household-nopop.json @@ -0,0 +1,94 @@ +{ + "id": "social-vulnerability-index-household-nopop", + "type": "Collection", + "title": "Social Vulnerability Index (Household) (Masked)", + "links": [], + "description": "Household Composition & Disability (Aged 65 or Older, Aged 17 or Younger, Civilian with a Disability, Single-Parent Households) - Percentile ranking \n\n ### Technical Details \n\n The Household Composition & Disability Score (HCDS) is one of the four themes used in determining a community’s social vulnerability. This dataset can be used to create a community evacuation plan accounting for individuals who have special needs, the elderly, and/or families with young children. In the event of a disaster, this data can also help responders determine the number of emergency personnel required for special household cases (accessibility assistance), the type of supplies needed based on age, and the amount of supplies, food, and other restorative resources needed¹. The HCDS SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC)was provided under the U.S. National Aeronautics and Space Administration (NASA)².", + "extent": { + "spatial": { + "bbox": [ + [ + -178.23333334, + 18.908332897999998, + -66.958333785, + 71.383332688 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2018-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "oranges", + "rescale": [ + [ + 0, + 1 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "ATSDR", + "url": "https://www.atsdr.cdc.gov/placeandhealth/svi/", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://nasa.gov/) (2018 Social Vulnerability Index (SVI) based on household and disability score)", + "href": "https://thumbnails.openveda.cloud/svi-household--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/social-vulnerability-index-household.json b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-household.json new file mode 100644 index 0000000..c6533fc --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-household.json @@ -0,0 +1,94 @@ +{ + "id": "social-vulnerability-index-household", + "type": "Collection", + "title": "Social Vulnerability Index (Household)", + "links": [], + "description": "Household Composition & Disability (Aged 65 or Older, Aged 17 or Younger, Civilian with a Disability, Single-Parent Households) - Percentile ranking \n\n ### Technical Details \n\n The Household Composition & Disability Score (HCDS) is one of the four themes used in determining a community’s social vulnerability. This dataset can be used to create a community evacuation plan accounting for individuals who have special needs, the elderly, and/or families with young children. In the event of a disaster, this data can also help responders determine the number of emergency personnel required for special household cases (accessibility assistance), the type of supplies needed based on age, and the amount of supplies, food, and other restorative resources needed¹. The HCDS SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC)was provided under the U.S. National Aeronautics and Space Administration (NASA)².", + "extent": { + "spatial": { + "bbox": [ + [ + -178.23333334, + 18.908332897999998, + -66.958333785, + 71.383332688 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2018-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "oranges", + "rescale": [ + [ + 0, + 1 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "ATSDR", + "url": "https://www.atsdr.cdc.gov/placeandhealth/svi/", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://nasa.gov/) (2018 Social Vulnerability Index (SVI) based on household and disability score)", + "href": "https://thumbnails.openveda.cloud/svi-household--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/social-vulnerability-index-housing-nopop.json b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-housing-nopop.json new file mode 100644 index 0000000..ad86c28 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-housing-nopop.json @@ -0,0 +1,94 @@ +{ + "id": "social-vulnerability-index-housing-nopop", + "type": "Collection", + "title": "Social Vulnerability Index (Housing) (Masked)", + "links": [], + "description": "Housing Type & Transportation (Multi-Unit Structures, Mobile Homes, Crowding, No Vehicle, Group Quarters) - Percentile ranking masked for regions with no population \n\n ### Technical Details \n\n The Housing Type & Transportation Score (HTTS) is one of the four themes used in determining a community’s social vulnerability, examining it against housing structure/type and vehicle access. As with the other SVI thematic areas, in the event of a disaster, or to better prepare for one, this dataset can help emergency personnel create an evacuation plan for individuals without vehicles, allocate emergency preparedness funding by community need, and identify areas in need of emergency shelters¹. It can also be used for local governments to identify areas needing more robust public transportation, areas of overcrowding, and local housing vulnerability. The HTTS SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC)was provided under the U.S. National Aeronautics and Space Administration (NASA)².", + "extent": { + "spatial": { + "bbox": [ + [ + -178.23333334, + 18.908332897999998, + -66.958333785, + 71.383332688 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2018-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "blues", + "rescale": [ + [ + 0, + 1 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "ATSDR", + "url": "https://www.atsdr.cdc.gov/placeandhealth/svi/", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://nasa.gov/) (2018 Social Vulnerability Index (SVI) based on housing type and transportation score)", + "href": "https://thumbnails.openveda.cloud/svi-housing--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/social-vulnerability-index-housing.json b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-housing.json new file mode 100644 index 0000000..b250daf --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-housing.json @@ -0,0 +1,94 @@ +{ + "id": "social-vulnerability-index-housing", + "type": "Collection", + "title": "Social Vulnerability Index (Housing)", + "links": [], + "description": "Housing Type & Transportation (Multi-Unit Structures, Mobile Homes, Crowding, No Vehicle, Group Quarters) - Percentile ranking \n\n ### Technical Details \n\n The Housing Type & Transportation Score (HTTS) is one of the four themes used in determining a community’s social vulnerability, examining it against housing structure/type and vehicle access. As with the other SVI thematic areas, in the event of a disaster, or to better prepare for one, this dataset can help emergency personnel create an evacuation plan for individuals without vehicles, allocate emergency preparedness funding by community need, and identify areas in need of emergency shelters¹. It can also be used for local governments to identify areas needing more robust public transportation, areas of overcrowding, and local housing vulnerability. The HTTS SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC)was provided under the U.S. National Aeronautics and Space Administration (NASA)².", + "extent": { + "spatial": { + "bbox": [ + [ + -178.23333334, + 18.908332897999998, + -66.958333785, + 71.383332688 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2018-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "blues", + "rescale": [ + [ + 0, + 1 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "ATSDR", + "url": "https://www.atsdr.cdc.gov/placeandhealth/svi/", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://nasa.gov/) (2018 Social Vulnerability Index (SVI) based on housing type and transportation score)", + "href": "https://thumbnails.openveda.cloud/svi-housing--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/social-vulnerability-index-minority-nopop.json b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-minority-nopop.json new file mode 100644 index 0000000..6a1f2ed --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-minority-nopop.json @@ -0,0 +1,94 @@ +{ + "id": "social-vulnerability-index-minority-nopop", + "type": "Collection", + "title": "Social Vulnerability Index (Minority) (Masked)", + "links": [], + "description": "Minority Status & Language (Minority, Speaks English “Less than Well”) - Percentile ranking \n\n ### Technical Details \n\n The Minority Status & Language Score (MSLS), as with the other SVI thematic areas, is used to calculate a community’s social vulnerability. This data set can be used to prepare emergency plans for communities with lower English-proficiency levels¹, and has helped contribute to efforts such as the Minority Health SVI and its related Dashboard. The Minority Health SVI is an extension of the CDC/ATSDR Social Vulnerability Index (CDC/ATSDR SVI), which is a database that helps emergency response planners and public health officials identify, map, and plan support for communities that will most likely need support before, during, and after a public health emergency². The MSLS SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC) was provided under the U.S. National Aeronautics and Space Administration (NASA)³.", + "extent": { + "spatial": { + "bbox": [ + [ + -178.23333334, + 18.908332897999998, + -66.958333785, + 71.383332688 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2018-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "purples", + "rescale": [ + [ + 0, + 1 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "ATSDR", + "url": "https://www.atsdr.cdc.gov/placeandhealth/svi/", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://nasa.gov/) (2018 Social Vulnerability Index (SVI) based on minority status and language score)", + "href": "https://thumbnails.openveda.cloud/svi-minority--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/social-vulnerability-index-minority.json b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-minority.json new file mode 100644 index 0000000..af29afa --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-minority.json @@ -0,0 +1,94 @@ +{ + "id": "social-vulnerability-index-minority", + "type": "Collection", + "title": "Social Vulnerability Index (Minority)", + "links": [], + "description": "Minority Status & Language (Minority, Speaks English “Less than Well”) - Percentile ranking \n\n ### Technical Details \n\n The Minority Status & Language Score (MSLS), as with the other SVI thematic areas, is used to calculate a community’s social vulnerability. This data set can be used to prepare emergency plans for communities with lower English-proficiency levels¹, and has helped contribute to efforts such as the Minority Health SVI and its related Dashboard. The Minority Health SVI is an extension of the CDC/ATSDR Social Vulnerability Index (CDC/ATSDR SVI), which is a database that helps emergency response planners and public health officials identify, map, and plan support for communities that will most likely need support before, during, and after a public health emergency². The MSLS SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC) was provided under the U.S. National Aeronautics and Space Administration (NASA)³.", + "extent": { + "spatial": { + "bbox": [ + [ + -178.23333334, + 18.908332897999998, + -66.958333785, + 71.383332688 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2018-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "purples", + "rescale": [ + [ + 0, + 1 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "ATSDR", + "url": "https://www.atsdr.cdc.gov/placeandhealth/svi/", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://nasa.gov/) (2018 Social Vulnerability Index (SVI) based on minority status and language score)", + "href": "https://thumbnails.openveda.cloud/svi-minority--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/social-vulnerability-index-overall-nopop.json b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-overall-nopop.json new file mode 100644 index 0000000..103da71 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-overall-nopop.json @@ -0,0 +1,94 @@ +{ + "id": "social-vulnerability-index-overall-nopop", + "type": "Collection", + "title": "Social Vulnerability Index (Overall) (Masked)", + "links": [], + "description": "Overall Social Vulnerability Index - Percentile ranking masked for areas with no population \n\n ### Technical Details \n\n The SVI Overall Score provides the overall, summed social vulnerability score for a given tract. The Overall Score SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC) was provided under the U.S. National Aeronautics and Space Administration (NASA)¹.", + "extent": { + "spatial": { + "bbox": [ + [ + -178.23333334, + 18.908332897999998, + -66.958333785, + 71.383332688 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2018-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "ylgnbu", + "rescale": [ + [ + 0, + 1 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "ATSDR", + "url": "https://www.atsdr.cdc.gov/placeandhealth/svi/", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://nasa.gov/) (2018 overall Social Vulnerability Index (SVI)", + "href": "https://thumbnails.openveda.cloud/svi-overall--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/social-vulnerability-index-overall.json b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-overall.json new file mode 100644 index 0000000..d0b092f --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-overall.json @@ -0,0 +1,94 @@ +{ + "id": "social-vulnerability-index-overall", + "type": "Collection", + "title": "Social Vulnerability Index (Overall)", + "links": [], + "description": "Overall Social Vulnerability Index - Percentile ranking \n\n ### Technical Details \n\n The SVI Overall Score provides the overall, summed social vulnerability score for a given tract. The Overall Score SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC) was provided under the U.S. National Aeronautics and Space Administration (NASA)¹.", + "extent": { + "spatial": { + "bbox": [ + [ + -178.23333334, + 18.908332897999998, + -66.958333785, + 71.383332688 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2018-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "ylgnbu", + "rescale": [ + [ + 0, + 1 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "ATSDR", + "url": "https://www.atsdr.cdc.gov/placeandhealth/svi/", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://nasa.gov/) (2018 overall Social Vulnerability Index (SVI)", + "href": "https://thumbnails.openveda.cloud/svi-overall--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/social-vulnerability-index-socioeconomic-nopop.json b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-socioeconomic-nopop.json new file mode 100644 index 0000000..2219658 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-socioeconomic-nopop.json @@ -0,0 +1,94 @@ +{ + "id": "social-vulnerability-index-socioeconomic-nopop", + "type": "Collection", + "title": "Social Vulnerability Index (SocioEconomic) (Masked)", + "links": [], + "description": "Socioeconomic Status (Below Poverty, Unemployed, Income, No High School Diploma) - Percentile ranking \n\n ### Technical Details \n\n The Economic Status Score, like the three other themes, is used in observing a community’s social vulnerability. As with other SVI scores, the economic status score can help local officials and teams identify communities that will need continued support to recover following an emergency or natural disaster¹. The Economic Status SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC) was provided under the U.S. National Aeronautics and Space Administration (NASA)².", + "extent": { + "spatial": { + "bbox": [ + [ + -178.23333334, + 18.908332897999998, + -66.958333785, + 71.383332688 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2018-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "greens", + "rescale": [ + [ + 0, + 1 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "ATSDR", + "url": "https://www.atsdr.cdc.gov/placeandhealth/svi/", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://nasa.gov/) (2018 Social Vulnerability Index (SVI) based on socioeconomic data", + "href": "https://thumbnails.openveda.cloud/svi-socioeconomic--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/social-vulnerability-index-socioeconomic.json b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-socioeconomic.json new file mode 100644 index 0000000..63551f4 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/social-vulnerability-index-socioeconomic.json @@ -0,0 +1,94 @@ +{ + "id": "social-vulnerability-index-socioeconomic", + "type": "Collection", + "title": "Social Vulnerability Index (SocioEconomic)", + "links": [], + "description": "Socioeconomic Status (Below Poverty, Unemployed, Income, No High School Diploma) - Percentile ranking \n\n ### Technical Details \n\n The Economic Status Score, like the three other themes, is used in observing a community’s social vulnerability. As with other SVI scores, the economic status score can help local officials and teams identify communities that will need continued support to recover following an emergency or natural disaster¹. The Economic Status SVI Grid is part of the U.S. Census Grids collection, and displays the Center for Disease Control & Prevention (CDC) SVI score. Funding for the final development, processing and dissemination of this data set by the Socioeconomic Data and Applications Center (SEDAC) was provided under the U.S. National Aeronautics and Space Administration (NASA)².", + "extent": { + "spatial": { + "bbox": [ + [ + -178.23333334, + 18.908332897999998, + -66.958333785, + 71.383332688 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2000-01-01T00:00:00Z", + "2018-12-31T00:00:00Z" + ] + ] + } + }, + "license": "MIT", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "year", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "greens", + "rescale": [ + [ + 0, + 1 + ] + ], + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "ATSDR", + "url": "https://www.atsdr.cdc.gov/placeandhealth/svi/", + "roles": [ + "producer", + "processor", + "licensor" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [NASA](https://nasa.gov/) (2018 Social Vulnerability Index (SVI) based on socioeconomic data", + "href": "https://thumbnails.openveda.cloud/svi-socioeconomic--dataset-cover.png", + "type": "image/png", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/production/collections_new_metadata/sport-lis-vsm0_100cm-percentile.json b/ingestion-data/production/collections_new_metadata/sport-lis-vsm0_100cm-percentile.json new file mode 100644 index 0000000..6072c71 --- /dev/null +++ b/ingestion-data/production/collections_new_metadata/sport-lis-vsm0_100cm-percentile.json @@ -0,0 +1,93 @@ +{ + "id": "sport-lis-vsm0_100cm-percentile", + "type": "Collection", + "title": "0-100 cm Volumetric Soil Moisture (%)", + "links": [], + "description": "The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Real-Time Land Information System (LIS). The Volumetric Soil Moisture product represents the actual moisture in a soil column from 0-100cm in depth. \n\n ### Technical Details \n\n The NASA Land Information System (LIS) is a high-performance land surface modeling and data assimilation system used to characterize land surface states and fluxes by integrating satellite-derived datasets, ground-based observations, and model re-analyses. The NASA SPoRT Center at MSFC developed a real-time configuration of the LIS (“SPoRT-LIS”), which is designed for use in experimental operations by domestic and international users. SPoRT-LIS is an observations-driven, historical and real-time modeling setup that runs the Noah land surface model over a full CONUS domain. It provides soil moisture estimates at approximately 3-km horizontal grid spacing over a 2-meter-deep soil column and has been validated for regional applications.", + "extent": { + "spatial": { + "bbox": [ + [ + -124.94000000000003, + 25.060000000000006, + -67.07000000000005, + 52.92999999999999 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2016-09-06T00:00:00Z", + "2016-11-29T00:00:00Z" + ] + ] + } + }, + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/render/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json" + ], + "item_assets": { + "cog_default": { + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + "roles": [ + "data", + "layer" + ], + "title": "Default COG Layer", + "description": "Cloud optimized default layer to display on map" + } + }, + "dashboard:is_periodic": false, + "dashboard:time_density": "day", + "stac_version": "1.0.0", + "renders": { + "dashboard": { + "resampling": "bilinear", + "bidx": [ + 1 + ], + "colormap_name": "rdylbu", + "rescale": [ + [ + 0, + 100 + ] + ], + "nodata": 9999.0, + "assets": [ + "cog_default" + ], + "title": "VEDA Dashboard Render Parameters" + } + }, + "providers": [ + { + "name": "NASA Short-term Prediction Research and Transition (SPoRT) Center", + "url": "https://geo.nsstc.nasa.gov/SPoRT/modeling/lis", + "roles": [ + "producer" + ] + }, + { + "name": "NASA VEDA", + "url": "https://www.earthdata.nasa.gov/dashboard/", + "roles": [ + "host" + ] + } + ], + "assets": { + "thumbnail": { + "title": "Thumbnail", + "description": "Photo by [Clay Banks](https://unsplash.com/photos/EdscD_R28bM) (Dry Clay Wall with Cracks)", + "href": "https://thumbnails.openveda.cloud/soil-moisture-main.jpg", + "type": "image/jpeg", + "roles": [ + "thumbnail" + ] + } + } +} \ No newline at end of file diff --git a/ingestion-data/staging/collections/eis_fire_fireline.json b/ingestion-data/staging/collections/eis_fire_fireline.json index d3ca147..7a2ce1e 100644 --- a/ingestion-data/staging/collections/eis_fire_fireline.json +++ b/ingestion-data/staging/collections/eis_fire_fireline.json @@ -51,8 +51,8 @@ "stac_version": "1.0.0", "providers": [ { - "name": "NASA National Oceanic and Atmospheric Administration", - "url": "https://www.nasa.gov/directorates/smd/joint-agency-satellite-division/noaa/", + "name": "NOAA", + "url": "https://www.noaa.gov", "roles": [ "producer" ] diff --git a/ingestion-data/staging/collections/eis_fire_newfirepix.json b/ingestion-data/staging/collections/eis_fire_newfirepix.json index 181d353..87fbe38 100644 --- a/ingestion-data/staging/collections/eis_fire_newfirepix.json +++ b/ingestion-data/staging/collections/eis_fire_newfirepix.json @@ -51,8 +51,8 @@ "stac_version": "1.0.0", "providers": [ { - "name": "NASA National Oceanic and Atmospheric Administration", - "url": "https://www.nasa.gov/directorates/smd/joint-agency-satellite-division/noaa/", + "name": "NOAA", + "url": "https://www.noaa.gov", "roles": [ "producer" ] diff --git a/ingestion-data/staging/collections/eis_fire_perimeter.json b/ingestion-data/staging/collections/eis_fire_perimeter.json index 9986dc4..d94faa2 100644 --- a/ingestion-data/staging/collections/eis_fire_perimeter.json +++ b/ingestion-data/staging/collections/eis_fire_perimeter.json @@ -51,8 +51,8 @@ "stac_version": "1.0.0", "providers": [ { - "name": "NASA National Oceanic and Atmospheric Administration", - "url": "https://www.nasa.gov/directorates/smd/joint-agency-satellite-division/noaa/", + "name": "NOAA", + "url": "https://www.noaa.gov", "roles": [ "producer" ]