eo-learn and InstaGeo-E2E-Geospatial-ML
EO-Learn is a general-purpose Earth observation processing framework that InstaGeo-E2E builds upon as a specialized end-to-end pipeline for multispectral data workflows, making them complementary rather than competitive tools.
About eo-learn
sentinel-hub/eo-learn
Earth observation processing framework for machine learning in Python
This tool helps Earth observation scientists and remote sensing experts extract valuable insights from satellite imagery. It takes raw spatio-temporal satellite data, processes it through automated workflows (like cloud masking or feature extraction), and outputs refined information suitable for analysis or machine learning models. It's designed for professionals working with large volumes of satellite data from programs like Copernicus and Landsat.
About InstaGeo-E2E-Geospatial-ML
instadeepai/InstaGeo-E2E-Geospatial-ML
A python package for end-to-end geospatial machine learning using multispectral earth observation data such as NASA HLS and ESA Sentinel-2.
This tool helps geospatial analysts and researchers automatically extract critical insights from satellite images. You can feed it multispectral earth observation data from sources like NASA HLS and ESA Sentinel-2, and it will output maps and predictions for things like flood zones, crop types, or even locust breeding grounds. It's designed for professionals who need to make data-driven decisions based on satellite imagery.
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