NYC Land Cover Pseudo-Segmentation and Analysis

With this project, you can turn your Jetson Nano 2GB into a tool to understand how a part of the planet's surface (in this case, NYC's Big Apple) has changed over time. Use the power of a ResNet-18 trained model to distinguish between ten different kinds of land cover, and track the percentage changes in land usage and composition over time with helpful charts. The land data for this project comes from the Sentinel Hub API, which is a cloud API for satellite imagery. The model was defined and trained to perform pseudo-segmentation, and it has an accuracy of 88%.