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Democratizing Open Machine Learning Technologies for Earth Observation

Democratizing Open Machine Learning Technologies for Earth Observation

Three inventions we’re working on at Radiant Earth Foundation
Go to the profile of Jed Sundwall
Jed Sundwall
Radiant MLHub Spotlight Q&A: Mohammad Alasawdah

Radiant MLHub Spotlight Q&A: Mohammad Alasawdah

Developing climate change related models and the importance of finding high-quality machine learning ready data sources
Go to the profile of Radiant Earth Foundation
Radiant Earth Foundation
Radiant Earth Foundation Publishes White Paper on Data Policies in Agriculture

Radiant Earth Foundation Publishes White Paper on Data Policies in ...

The white paper explores a data ethics framework to preemptively address farmers’ concerns in low- and middle-income countries.
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Radiant Earth Foundation
Latest stories
Azavea’s server, Franklin, now supports the latest STAC API

Azavea’s server, Franklin, now supports the latest STAC API

The changes in this latest deployment ensure a slim, easy-to-use STAC spec service.
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Radiant Earth Foundation
ii2030 Challenge: AI for Earth Observation. Who are the users?

ii2030 Challenge: AI for Earth Observation. Who are the users?

Discover data usage scenarios for open machine learning ready Earth observation repositories like Radiant MLHub.
Go to the profile of Radiant Earth Foundation
Radiant Earth Foundation
Radiant MLHub Spotlight Q&A: Emmanuel Siaw-Darko

Radiant MLHub Spotlight Q&A: Emmanuel Siaw-Darko

Building baseline models for data scientists to train, validate and test the accuracy of algorithms
Go to the profile of Radiant Earth Foundation
Radiant Earth Foundation
Workshop: Artificial Intelligence and the Environment from the Global South

Workshop: Artificial Intelligence and the Environment from the Global South

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Radiant Earth Foundation
Announcing Executive Leadership Transition

Announcing Executive Leadership Transition

By Radiant Earth Foundation Board of Directors
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Radiant Earth Foundation
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Cloud Optimized GeoTIFF Advances

Cloud Optimized GeoTIFF Advances

The last month has seen a number of great Cloud Optimized GeoTIFF advances, with lots of enthusiasm at the FOSS4G-NA conference.
Go to the profile of Chris Holmes
Chris Holmes
A Guide for Collecting and Sharing Ground Reference Data for Machine Learning Applications

A Guide for Collecting and Sharing Ground Reference Data for Machine Learning Applications

Five criteria for making ground reference data ready for Earth Observation machine learning models
Go to the profile of Radiant Earth Foundation
Radiant Earth Foundation
Exploiting Multi-Region Data Locality with Lambda@Edge

Exploiting Multi-Region Data Locality with Lambda@Edge

Lambda@Edge makes tiles.rdnt.io faster (and cheaper). Here’s how.
Go to the profile of Seth Fitzsimmons
Seth Fitzsimmons
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