Radiant MLHub

Open Library for Earth Observations Machine Learning

Radiant MLHub is the world’s first cloud-based open library dedicated to Earth observation training data and models for use with machine learning algorithms.

Radiant MLHub hosts open ML training datasets and models generated by Radiant Earth Foundation, partners, and community. Radiant MLHub allows anyone to access, store, register, and share open training datasets and models for high-quality Earth observations, and it’s designed to encourage widespread collaboration and development of trustworthy applications.

Browse Datasets by Application

Community of Practice

Community of Practice

Radiant MLHub facilitates an open community commons for geospatial training data, machine learning models, and standards to encourage collaboration and share information. Find out how you can get involved.

API and Python Client

API and Python Client

The Python client allows users to search and download geospatial training data on Radiant MLHub without managing API requests. Or users may apply MLHub with other scripting languages using our REST API. View the Python quick-start and Jupyter Notebooks in the Documentation section.

Geospatial Machine Learning Model Catalog

ML Model Catalog Specification

Radiant Earth is developing the ML Model Extension to the SpatioTemporal Asset Catalog (STAC) which will empower users to discover and access existing repositories of ML models for various geospatial applications. Read more about the ML Model Extension.

STAC Ecosystem

STAC Ecosystem

All Radiant MLHub geospatial training data collections are stored using a SpatioTemporal Asset Catalog (STAC) compliant catalogs, and exposed through a common API. Learn more about STAC.