Radiant Earth

Radiant Earth Increasing shared understanding of the world by expanding access to geospatial data and ML models.

We are excited to announce our latest   on Zindi, together with the U.S. Department of Agriculture Foreign Agricultural ...
11/21/2022

We are excited to announce our latest on Zindi, together with the U.S. Department of Agriculture Foreign Agricultural Service (FAS), USAID - US Agency for International Development, and NASA Harvest!
👩🏽‍💻Join top coders around the world to detect crop field boundaries for smallholder farmers using multispectral observations
💰$5,000 in cash prizes
Register here 👉🏽 https://zindi.africa/competitions/nasa-harvest-field-boundary-detection-challenge

🆕   Can you detect crop types in agricultural fields from a satellite image? Bring your   skills and join this data chal...
10/14/2022

🆕
Can you detect crop types in agricultural fields from a satellite image? Bring your skills and join this data challenge to classify crops in fields across various districts in the Northern states of Uttar Pradesh, Rajasthan, Odisha, and Biharcities 🇮🇳
👉🏽 https://zindi.africa/competitions/agrifieldnet-india-challenge

Radiant Earth is excited to announce the release of LandCoverNet, the first global multi-satellite training dataset for ...
07/11/2022

Radiant Earth is excited to announce the release of LandCoverNet, the first global multi-satellite training dataset for land cover classification. will enable the creation of high-resolution & up-to-date maps for natural resource management http://bit.ly/3nVxdhE

NASA - National Aeronautics and Space Administration, Microsoft, Schmidt Futures, Sinergi Foundation

🎉 We're excited to announce the release of LandCoverNet South America, a human-labeled   classification   for the region...
04/25/2022

🎉 We're excited to announce the release of LandCoverNet South America, a human-labeled classification for the region.🌎

🔗 Now available for download on https://mlhub.earth/data/landcovernet_sa_v1

The AI4EO   Challenge has come to a fruitful end with our partners Planet, ESA - European Space Agency, Deutsches Zentru...
03/17/2022

The AI4EO Challenge has come to a fruitful end with our partners Planet, ESA - European Space Agency, Deutsches Zentrum für Luft- und Raumfahrt (DLR), TUM Technische Universität München! We are excited to showcase the top 4 solutions alongside our keynote speaker from NASA Harvest, Dr. Hannah Kerner Machine Learning Lead & U.S. Domestic Co-Lead, on April 6th!

Register now to learn about the future of food security! https://learn.planet.com/ai4eo-food-security-challenge-registration.html?utm_source=partner radientearthfoundation&utm_medium=referral&utm_campaign=ag&utm_content=ag-webinar-ai4eo-awards

Address

740 15th Street NW, Suite 900
Washington D.C., DC
20005

Opening Hours

Monday 9:30am - 6:30pm
Tuesday 9:30am - 6:30pm
Wednesday 9:30am - 6:30pm
Thursday 9:30am - 6:30pm
Friday 9:30am - 6:30pm

Telephone

+12025963603

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Why we exist

We like to think of Radiant Earth Foundation as a launch pad. However, instead of a rocket lifting into space, we propel data scientists, programmers and the larger geospatial community into an illuminated world of training data, models, and standards for different applications to support decision-makers working on global development challenges. Just as rockets enable the unique perspective of looking at the Earth from space, Radiant Earth Foundation enables expert users to combine machine learning and Earth observation for innovation and solution designs to meet the Sustainable Development Goals – the world’s most critical challenges.

Mission Radiant Earth Foundation's mission is to empower organizations and individuals globally with training data and tools, and, to cultivate a community focused on applying machine learning on Earth observations to meet the Sustainable Development Goals – the world’s most critical challenges.

Vision Radiant Earth Foundation's vision is to combine machine learning and Earth observation for positive global impact.