Radiant Earth Foundation

{{Short description|US nonprofit organization}}

{{expert needed |Computer science|reason=more secondary sources needed|date=October 2020}}

Radiant Earth Foundation is an American non-profit organization founded in 2016.{{Cite news|last=Totaro|first=Paola|date=3 March 2017|title=Daten für alle – Gates startet Satelliten-Projekt|work=Reuters Weltnachrichten|url=https://www.reuters.com/article/usa-satelliten-bill-gates-idDEKBN16A13U|access-date=9 October 2020}}{{Cite news|date=2020|title=Radiant Earth Annual Report 2019|url=https://s3-us-west-2.amazonaws.com/radiant-blog-assets/wp-content/uploads/2020/04/15230328/2019-Annual-Report.pdf}} Its goal is to apply machine learning for Earth observation{{Cite book|last=Demyanov|first=Vladislav|title=Satellites Missions and Technologies for Geosciences|publisher=IntechOpen|year=2020|isbn=978-1-78985-995-9|pages=117}} to meet the Sustainable Development Goals.{{Cite web|title=Radiant Earth Foundation|url=http://www.data4sdgs.org/partner/radiant-earth-foundation|access-date=2020-08-27|website=www.data4sdgs.org}} The foundation works on developing openly licensed Earth observation machine learning libraries, training data sets{{cite arXiv|last=Nachmany|first=Yoni|date=14 November 2018|title=Generating a Training Dataset for Land Cover Classification to Advance Global Development|class=cs.CV|eprint=1811.07998}} and models through an open source hub{{Cite journal|last=Zenke da Cruz|first=Camila Lauria|date=2019|title=Radiant Earth Platform: POTENCIALIDADES E LIMITAÇÕES DE ABORDAGEM DE PROCESSAMENTO DIGITAL DE IMAGEM NA NUVEM|url=http://marte2.sid.inpe.br/col/sid.inpe.br/marte2/2019/10.08.13.18/doc/97805.pdf|journal=Anais do XIX Simpósio Brasileiro de Sensoriamento Remoto|isbn=978-85-17-00097-3}} that support missions worldwide{{Cite web|title=Radiant Earth Foundation Releases First Earth Imagery Platform for Global Development – Tanzania News Gazette|url=https://www.tanzanianewsreports.com/radiant-earth-foundation-releases-first-earth-imagery-platform-for-global-development/|access-date=2020-10-09|language=en-US}} like agriculture,{{Cite journal|last=Ballantynwe|first=A.|date=2019|title=Benchmark Agricultural Training Datasets to Create Regional Crop Type Classification Models from Earth Observations|url=https://ui.adsabs.harvard.edu/abs/2019AGUFMGC23H1439B/abstract|journal=American Geophysical Union, Fall Meeting 2019, Abstract #GC23H-1439|volume=2019|pages=GC23H–1439|bibcode=2019AGUFMGC23H1439B}} conservation, and climate change.{{Cite web|title=About – Radiant Earth Foundation|url=https://www.radiant.earth/about/|access-date=2020-08-27|language=en-US}} Radiant Earth also works on a community of practice that develop standards, templates and APIs around machine learning for Earth observation. According to scholar David Lindgren, the foundation "serves to make satellite imagery widely accessible and usable for development practitioners".{{Citation|last=Lindgren|first=David|title=Satellites and Their Potential Role in Supporting the African Union's Continental Early Warning System|date=2020|url=https://doi.org/10.1007/978-3-030-32930-3_13|work=Space Fostering African Societies: Developing the African Continent through Space, Part 1|pages=195–205|editor-last=Froehlich|editor-first=Annette|series=Southern Space Studies|place=Cham|publisher=Springer International Publishing|language=en|doi=10.1007/978-3-030-32930-3_13|isbn=978-3-030-32930-3|s2cid=213700549|access-date=2020-10-26|url-access=subscription}}

The Foundation is funded by Schmidt Futures, Bill & Melinda Gates Foundation, McGovern Foundation and the Omidyar network