Radiant Earth Foundation
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Radiant Earth Foundation is an American non-profit organization founded in 2016.[1] Its goal is to apply machine learning for Earth observation[2] to meet the Sustainable Development Goals.[3] The foundation works on developing openly licensed Earth observation machine learning libraries, training data sets[4] and models through an open source hub that support missions worldwide[5] like agriculture[6], conservation, and climate change.[7] Radiant Earth also works on a community of practice that develop standards around machine learning for Earth observation.
The Foundation is funded by Schmidt Futures, Bill & Melinda Gates Foundation, McGovern Foundation and the Omidyar network[8]
See also
- Earth Observation – Information about the Earth environment, remote or in situ
- Machine learning – Study of algorithms that improve automatically through experience
- Big data – Extremely large or complex datasets
- List of datasets for machine learning research
Notes
- ^ "Radiant Earth Annual Report 2019" (PDF). 2020.
{{cite news}}: CS1 maint: url-status (link) - ^ Demyanov, Vladislav (2020). Satellites Missions and Technologies for Geosciences. IntechOpen. p. 117. ISBN 978-1-78985-995-9.
- ^ "Radiant Earth Foundation". www.data4sdgs.org. Retrieved 2020-08-27.
- ^ Nachmany, Yoni (14 November 2018). "Generating a Training Dataset for Land Cover Classification to Advance Global Development" (PDF). arXiv:1811.07998.
- ^ "Radiant Earth Foundation Releases First Earth Imagery Platform for Global Development – Tanzania News Gazette". Retrieved 2020-10-09.
- ^ Ballantynwe, A. (2019). "Benchmark Agricultural Training Datasets to Create Regional Crop Type Classification Models from Earth Observations". American Geophysical Union, Fall Meeting 2019, abstract #GC23H-1439.
- ^ "About – Radiant Earth Foundation". Retrieved 2020-08-27.
- ^ "About – Radiant Earth Foundation". Retrieved 2020-08-27.
External links
- "Radiant Earth Foundation – Earth Imagery for Impact". radiant.earth. Retrieved 2020-08-27.
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