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Radiant MLHub

cog earth observation environmental geospatial labeled machine learning satellite imagery stac


Radiant MLHub is an open library for geospatial training data that hosts datasets generated by Radiant Earth Foundation's team as well as other training data catalogs contributed by Radiant Earth’s partners. Radiant MLHub is open to anyone to access, store, register and/or share their training datasets for high-quality Earth observations. All of the training datasets are stored using a SpatioTemporal Asset Catalog (STAC) compliant catalog and exposed through a common API. Training datasets include pairs of imagery and labels for different types of machine learning problems including image classification, object detection, and semantic segmentation. Labels are generated from ground reference data and/or image annotation.

Update Frequency

New training data catalogs are added on a rolling basis


Access to Radiant MLHub data is free for everyone. Each dataset has its own license (usually CC-BY or CC-BY-SA). View Terms of Service.


Managed By

See all datasets managed by Radiant Earth Foundation.


How to Cite

Radiant MLHub was accessed on DATE from

Usage Examples

Tools & Applications

Resources on AWS

  • Description
    Radiant MLHub Training Data
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    AWS Region
    AWS CLI Access (No AWS account required)
    aws s3 ls --no-sign-request s3://radiant-mlhub/

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