This repo contains example analyses conducted by Defenders of Wildlife using the Google Earth Engine platform.
We have developed several publicly available apps using the Google Earth Engine App Developer focusing on automatically mapping and quantifying changes to the landscape over time. The first of these assesses deforestation due to Logging over time on Prince of Wales Island in the Tongass National Forest
Another example measured coastal habitat loss for several Threatened and Endangered species following Hurricane Michael
The Nature Conservancy is interested in modelling the impact of the proliferation of ground-mounted solar energy development on wildlife habitat and connectivity in North Carolina.
We used Sentinel-2 multispectral imagery and Sentinel-1 SAR data to classify the state into Forest, Ag/Pasture, Impervious, Water, and Solar. Using a random forest classifier, we achieved a Kappa accuracy of 0.84. In the images below, black areas are the places our model identified as solar panels
Long Island is exploring options for developing utility scale renewable energy as New York State strives to achieve its 50% renewable energy by 2030 goals. In order to promote renewable energy development and habitat conservation, we were interested in finding low-impact sites for solar development on Long Island - and parking lots present an ideal case. However, a comprehensive map of parking lots across the entire Island is currently unavailable.
In this analysis we again used a random forest classifier applied to Sentinel-1 and Sentinel-2 data.
