Creating a model to predict species movement with data from Cornell's eBird database
Accessed csv file of eBird Observation Dataset from Cornell Lab of Ornithology on Global Biodiversity Information Facility (GBIF) website: https://www.gbif.org/dataset/4fa7b334-ce0d-4e88-aaae-2e0c138d049e
Created a csv file model_birddata.csv (see Birds-Database repo) with relevant data from original file and some feature engineered parameters (X,Y,Z coordinates and Absolute Date)
Plotted maps of sighting and further analysis to come in birds_model.py
Plot of bird sightings across the globe (based on X,Y,Z coordinates calculated from Latitude and Longitude). View is from the top of
the globe, with North Pole labelled:
Plot of bird sightings across the world:
Histogram of sightings over time:
Sightings of a particular species of bird over the world. This function can be called to view the sightings of any
specified species. Color of points moves from yellow to the red, with yellow being the least recent and red being the
most recent sighting:
