Popular GitHub Repositories for Geospatial Data

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

A project for the development of rich geospatial data from the city of São Paulo for use in Machine Learning models.

Training data generation for cloud gap imputation fine-tuning of Prithvi Geospatial Foundation Model

Predict landslides using logistic regression, xgboost, and neural network.