Adding new external datasets

GHS pop and bu, Critical Infrastructures global exposure

_datasets/ghs-built-up-surface-grid-multitemporal-1975-2030.md

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+---
+contact_point:
+  email: [email protected]
+  name: JRC GHSL
+  url: https://data.jrc.ec.europa.eu/dataset/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea
+creator:
+  name: EC Joint Research Centre
+  url: https://human-settlement.emergency.copernicus.eu/ghs_buS2023.php
+dataset_id: GHSL_BU-S
+description: The spatial raster dataset depicts the distribution of the built-up (BU)
+  surfaces estimates between 1975 and 2030 in 5 years intervals and two functional
+  use components a) the total BU surface and b) the non-residential (NRES) BU surface.
+  The data is made by spatial-temporal interpolation of five observed collections
+  of multiple-sensor, multiple-platform satellite imageries. Landsat (MSS, TM, ETM
+  sensor) supports the 1975, 1990, 2000, and 2014 epochs. Sentinel2 (S2) composite
+  (GHS-composite-S2 R2020A) supports the 2018 epoch.
+details: "The built-up surface fraction (BUFRAC) is estimated at 10m of spatial resolution\
+  \ from the S2 image data, using as learning set a composite of data from GHS-BUILT-S2\
+  \ R2020A, Facebook, Microsoft, and Open Street Map (OSM) building delineation. The\
+  \ BUFRAC inference is made from the combination of quantized image features (reflectance,\
+  \ derivative of morphological profile DMP) through associative rule learning applied\
+  \ to spatial data analytics, which was introduced as symbolic machine learning (SML).\
+  \ The non-residential (NRES) domain is predicted from S2 image data by observation\
+  \ of radiometric, textural, and morphological features in an object-oriented image\
+  \ processing framework. The multi-temporal dimension is provided by testing by the\
+  \ SML the association between the combination of the quantized radiometric information\
+  \ collected by the Landsat imagery in the past epochs, and the \u201Cbuilt-up\u201D\
+  \ (BU) and \u201Cnon-built-up\u201D (NBU) class abstraction on image segments extracted\
+  \ from S2 images. The spatial-temporal interpolation is solved by rank-optimal spatial\
+  \ allocation using explanatory variables related to the landscape (slope, elevation,\
+  \ distance to water, and distance to vegetation) and related to the observed dynamic\
+  \ of BU surfaces in the past epochs."
+exposure:
+  category: buildings
+  dimension: structure
+  quantity_kind: area
+  taxonomy: null
+hazard: null
+license: CC-BY-4.0
+loss: null
+project: GHSL - Global Human Settlement Layer
+publisher:
+  name: JRC
+  url: https://human-settlement.emergency.copernicus.eu/
+purpose: null
+resources:
+- coordinate_system: ESRI:54009
+  description: The spatial raster dataset depicts the distribution of built-up surfaces,
+    expressed as number of square metres. The data report about the total built-up
+    surface and the built-up surface allocated to dominant non-residential (NRES)
+    uses. The product is available for different epochs, resolutions and coordinate
+    systems, but not all the combinations are available.
+  download_url: https://human-settlement.emergency.copernicus.eu/download.php?ds=bu
+  format: geotiff
+  id: '0'
+  spatial_resolution: null
+  title: GHS built-up surface (R2023)
+risk_data_type:
+- exposure
+schema: rdl-02
+spatial:
+  countries:
+  - GLO
+  scale: global
+title: GHS built-up surface grid multitemporal (1975-2030)
+version: R2023
+vulnerability: null
+---

_datasets/ghs-population-grid-multitemporal-1975-2030.md

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+---
+contact_point:
+  email: [email protected]
+  name: JRC GHSL
+  url: https://data.jrc.ec.europa.eu/dataset/2ff68a52-5b5b-4a22-8f40-c41da8332cfe
+creator:
+  name: EC Joint Research Centre
+  url: https://human-settlement.emergency.copernicus.eu/ghs_pop2023.php
+dataset_id: GHSL_POP
+description: 'The spatial raster dataset depicts the distribution of residential population,
+  expressed as the number of people per cell. Residential population estimates between
+  1975 and 2020 in 5-year intervals and projections to 2025 and 2030 derived from
+  CIESIN GPWv4.11 were disaggregated from census or administrative units to grid cells,
+  informed by the distribution, volume, and classification of built-up as mapped in
+  the Global Human Settlement Layer (GHSL) global layer per corresponding epoch. '
+details: 'This dataset is an update of the product released in 2022. Major improvements
+  are the following: use of built-up volume maps (GHS-BUILT-V R2022A); use of more
+  recent and detailed population estimates derived from GPWv4.11 integrating both
+  UN World Population Prospects 2022 country population data and World Urbanisation
+  Prospects 2018 data on Cities; revision of GPWv4.11 population growthrates by convergence
+  to upper administrative level growthrates; systematic improvement of census coastlines;
+  systematic revision of census units declared as unpopulated; integration of non-residential
+  built-up volume information (GHS-BUILT-V_NRES R2023A); spatial resolution of 100m
+  Mollweide (and 3 arcseconds in WGS84); projections to 2030.'
+exposure:
+  category: population
+  dimension: population
+  quantity_kind: count
+  taxonomy: null
+hazard: null
+license: CC-BY-4.0
+loss: null
+project: GHSL - Global Human Settlement Layer
+publisher:
+  name: JRC
+  url: https://human-settlement.emergency.copernicus.eu/
+purpose: null
+resources:
+- coordinate_system: ESRI:54009
+  description: The product is available for different epochs, resolutions and coordinate
+    systems, but not all the combinations are available.
+  download_url: https://human-settlement.emergency.copernicus.eu/download.php?ds=pop
+  format: geotiff
+  id: '0'
+  spatial_resolution: null
+  title: GHS population grid (R2023)
+risk_data_type:
+- exposure
+schema: rdl-02
+spatial:
+  countries:
+  - GLO
+  scale: global
+title: GHS population grid multitemporal (1975-2030)
+version: R2023
+vulnerability: null
+---

_datasets/global-dataset-of-critical-infrastructure.md

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+---
+contact_point:
+  email: [email protected]
+  name: Sadhana Nirandjan
+creator:
+  email: [email protected]
+  name: Sadhana Nirandjan
+dataset_id: GLB-CI
+description: The spatially-explicit harmonized global dataset of critical infrastructure
+  (CI) contains data on the amount of infrastructure per infrastructure type and the
+  Critical Infrastructure Spatial Index (CISI)
+details: null
+exposure:
+  category: infrastructure
+  dimension: structure
+  quantity_kind: area
+  taxonomy: null
+hazard: null
+license: CC-BY-4.0
+loss: null
+project: null
+publisher:
+  name: Institute for Environmental Studies (IVM)
+  url: https://vu.nl/en/about-vu/research-institutes/ivm
+purpose: null
+resources:
+- coordinate_system: EPSG:4326
+  description: Amount of infrastructure per infrastructure type at a resolution of
+    0.10x0.10 and 0.25x0.25 degrees.
+  download_url: https://zenodo.org/records/4957647/files/Amount_of_infrastructure.zip?download=1
+  format: geotiff
+  id: AoI
+  spatial_resolution: 11132
+  title: Amount of infrastructure
+- coordinate_system: EPSG:4326
+  description: Critical Infrastructure Spatial Index (CISI) as a combination of individual
+    infrastracture categories at a resolution of 0.10x0.10 and 0.25x0.25 degrees
+  download_url: https://zenodo.org/records/4957647/files/CISI.zip?download=1
+  format: geotiff
+  id: CISI
+  spatial_resolution: 11132
+  title: Critical Infrastructure Spatial Index (CISI)
+risk_data_type:
+- exposure
+schema: rdl-02
+spatial:
+  countries:
+  - GLO
+  scale: global
+title: A spatially-explicit harmonized global dataset of critical infrastructure
+version: '1'
+vulnerability: null
+---

_datasets/json/global-critical-infrastructure-exposure.json

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+{
+    "datasets": [
+        {
+            "id": "GLB-CI",
+            "title": "A spatially-explicit harmonized global dataset of critical infrastructure",
+            "description": "The spatially-explicit harmonized global dataset of critical infrastructure (CI) contains data on the amount of infrastructure per infrastructure type and the Critical Infrastructure Spatial Index (CISI)",
+            "risk_data_type": [
+                "exposure"
+            ],
+            "publisher": {
+                "name": "Institute for Environmental Studies (IVM)",
+                "url": "https://vu.nl/en/about-vu/research-institutes/ivm"
+            },
+            "version": "1",
+            "spatial": {
+                "scale": "global"
+            },
+            "license": "CC-BY-4.0",
+            "contact_point": {
+                "name": "Sadhana Nirandjan",
+                "email": "[email protected]"
+            },
+            "creator": {
+                "name": "Sadhana Nirandjan",
+                "email": "[email protected]"
+            },
+            "exposure": {
+                "category": "infrastructure",
+                "metrics": [
+                    {
+                        "id": "0",
+                        "dimension": "structure",
+                        "quantity_kind": "area"
+                    }
+                ]
+            },
+            "attributions": [
+                {
+                    "id": "0",
+                    "entity": {
+                        "name": "Sadhana Nirandjan",
+                        "email": "[email protected]"
+                    },
+                    "role": "author"
+                },
+                {
+                    "id": "1",
+                    "entity": {
+                        "name": "Institute for Environmental Studies (IVM)",
+                        "url": "https://vu.nl/en/about-vu/research-institutes/ivm"
+                    },
+                    "role": "distributor"
+                }
+            ],
+            "referenced_by": [
+                {
+                    "id": "0",
+                    "name": "A spatially-explicit harmonized global dataset of critical infrastructure ",
+                    "author_names": [
+                        "Sadhana Nirandjan",
+                        "Elco E Koks",
+                        "Philip J Ward",
+                        "Jeroen C J H Aerts"
+                    ],
+                    "date_published": "2022-04-01",
+                    "url": "https://www.nature.com/articles/s41597-022-01218-4",
+                    "doi": "10.1038/s41597-022-01218-4 "
+                }
+            ],
+            "resources": [
+                {
+                    "id": "AoI",
+                    "title": "Amount of infrastructure",
+                    "description": "Amount of infrastructure per infrastructure type at a resolution of 0.10x0.10 and 0.25x0.25 degrees.",
+                    "format": "geotiff",
+                    "spatial_resolution": 11132,
+                    "coordinate_system": "EPSG:4326",
+                    "access_url": "https://zenodo.org/records/4957647#.YlPdTChBw2w",
+                    "download_url": "https://zenodo.org/records/4957647/files/Amount_of_infrastructure.zip?download=1"
+                },
+                {
+                    "id": "CISI",
+                    "title": "Critical Infrastructure Spatial Index (CISI)",
+                    "description": "Critical Infrastructure Spatial Index (CISI) as a combination of individual infrastracture categories at a resolution of 0.10x0.10 and 0.25x0.25 degrees",
+                    "format": "geotiff",
+                    "spatial_resolution": 11132,
+                    "coordinate_system": "EPSG:4326",
+                    "access_url": "https://zenodo.org/records/4957647#.YlPdTChBw2w",
+                    "download_url": "https://zenodo.org/records/4957647/files/CISI.zip?download=1"
+                }
+            ],
+            "links": [
+                {
+                    "href": "https://docs.riskdatalibrary.org/en/0__2__0/rdls_schema.json",
+                    "rel": "describedby"
+                }
+            ]
+        }
+    ]
+}

_datasets/json/global-critical-infrastructure-vulnerability.json

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+{
+    "datasets": [
+        {
+            "id": "GLB-CI_vln",
+            "title": "Physical Vulnerability Database for Critical Infrastructure Hazard Risk Assessments",
+            "description": "The Physical Vulnerability Database for Critical Infrastructure Hazard Risk Assements is a database that contains fragility and vulnerability curves that can be used to evaluate the expected or potential damages to infrastructure assets due to flooding, earthquakes, windstorms and landslides. The curves have been obtained from various literature studies, and as such they have different individual attributes (e.g. type of function, approach, cost type).",
+            "risk_data_type": [
+                "vulnerability"
+            ],
+            "publisher": {
+                "name": "Institute for Environmental Studies (IVM)",
+                "url": "https://vu.nl/en/about-vu/research-institutes/ivm"
+            },
+            "version": "1",
+            "spatial": {
+                "scale": "global"
+            },
+            "license": "CC-BY-4.0",
+            "contact_point": {
+                "name": "Sadhana Nirandjan",
+                "email": "[email protected]"
+            },
+            "creator": {
+                "name": "Sadhana Nirandjan",
+                "email": "[email protected]"
+            },
+            "attributions": [
+                {
+                    "id": "0",
+                    "entity": {
+                        "name": "Sadhana Nirandjan",
+                        "email": "[email protected]"
+                    },
+                    "role": "author"
+                },
+                {
+                    "id": "1",
+                    "entity": {
+                        "name": "Institute for Environmental Studies (IVM)",
+                        "url": "https://vu.nl/en/about-vu/research-institutes/ivm"
+                    },
+                    "role": "distributor"
+                }
+            ],
+            "referenced_by": [
+                {
+                    "id": "0",
+                    "name": "Review article: Physical Vulnerability Database for Critical Infrastructure Multi-Hazard Risk Assessments – A systematic review and data collection",
+                    "author_names": [
+                        "Sadhana Nirandjan",
+                        "Elco E Koks",
+                        "Mengqi Ye",
+                        "Raghav Pant",
+                        "Kees C H van Ginkel",
+                        "Jeroen C J H Aerts",
+                        "Philip J Ward"
+                    ],
+                    "date_published": "2024-01-23",
+                    "url": "https://nhess.copernicus.org/preprints/nhess-2023-208/",
+                    "doi": "doi.org/10.5194/nhess-2023-208"
+                }
+            ],
+            "resources": [
+                {
+                    "id": "D1",
+                    "title": "Table D1",
+                    "description": "Summary table with information on hazard, exposure, and vulnerability characteristics as well as a number of details regarding reliability and reference purposes.",
+                    "format": "xlsx",
+                    "access_url": "https://zenodo.org/records/10203846",
+                    "download_url": "https://zenodo.org/records/10203846/files/Table_D1_Summary_CI_Vulnerability_Data_V1.0.0.xlsx?download=1"
+                },
+                {
+                    "id": "D2",
+                    "title": "Table D2",
+                    "description": "Collection of fragility and vulnerability curves",
+                    "format": "xlsx",
+                    "access_url": "https://zenodo.org/records/10203846",
+                    "download_url": "https://zenodo.org/records/10203846/files/Table_D2_Multi-Hazard_Fragility_and_Vulnerability_Curves_V1.0.0.xlsx?download=1"
+                },
+                {
+                    "id": "D3",
+                    "title": "Table D3",
+                    "description": "Cost values that can be used in combination with the curves for the estimation of asset damages",
+                    "format": "xlsx",
+                    "access_url": "https://zenodo.org/records/10203846",
+                    "download_url": "https://zenodo.org/records/10203846/files/Table_D3_Costs_V1.0.0.xlsx?download=1"
+                }
+            ],
+            "vulnerability": {
+                "cost": [
+                    {
+                        "id": "0",
+                        "dimension": "structure",
+                        "unit": "EUR"
+                    }
+                ]
+            },
+            "links": [
+                {
+                    "href": "https://docs.riskdatalibrary.org/en/0__2__0/rdls_schema.json",
+                    "rel": "describedby"
+                }
+            ]
+        }
+    ]
+}