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Radiant Earth Insights
Helping the global development community navigate the Machine Learning and Earth observation marketplace and innovations taking place.
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Socially Responsible Data Labeling
Socially Responsible Data Labeling
Generating a global training dataset while supporting social initiatives and sustainable practices
Radiant Earth Foundation
Apr 12
Ashiraf Nsibambi Kyabainze: Technology and Social Entrepreneurship in Uganda
Ashiraf Nsibambi Kyabainze: Technology and Social Entrepreneurship ...
A conversation about using technology for a smart value chain to boldly impact food insecurity in Uganda
Radiant Earth Foundation
Apr 12
Igor Ivanov: Harnessing Machine Learning Skills to Reduce Damages from Tropical Storms
Igor Ivanov: Harnessing Machine Learning Skills to Reduce Damages f...
A conversation with the First Place winner of the Radiant Earth Tropical Cyclone Wind Estimation Data Competition
Radiant Earth Foundation
Apr 12
Latest stories
Radiant MLHub Python Client — Beta Release
Radiant MLHub Python Client — Beta Release
Using the Python client to discover and download training datasets without managing API requests.
Jon Duckworth
Mar 16
SpatioTemporal Asset Catalog (STAC) 1.0.0-rc.1 Released
SpatioTemporal Asset Catalog (STAC) 1.0.0-rc.1 Released
The STAC community is pleased to announce the final release before we lock in for long term stability. Please test it out and give…
Chris Holmes
Mar 10
Celebrating Women Leading the ML4EO Community
Celebrating Women Leading the ML4EO Community
Meet the women around the world at the forefront of machine learning for Earth observation.
Radiant Earth Foundation
Mar 8
The Path to STAC 1.0.0
The Path to STAC 1.0.0
The STAC Community’s plan to get to 1.0.0 soon. We’re forming a Project Steering Committee and seeking sponsorship for the final push.
Chris Holmes
Feb 18
Archived Training Dataset Downloads now Available on Radiant MLHub
Archived Training Dataset Downloads now Available on Radiant MLHub
A little over a year ago we launched the first iteration of Radiant MLHub in the form of a STAC-compliant API which allows you to browse…
Kevin Booth
Feb 8
Radiant MLHub in 2021: Realizing an Ecosystem
Radiant MLHub in 2021: Realizing an Ecosystem
Radiant MLHub fills the gap in the ecosystem to facilitate publication and uptake of training datasets in our community.
Radiant Earth Foundation
Jan 27
Announcing the Updated Machine Learning for Earth Observation Market Map
Announcing the Updated Machine Learning for Earth Observation Market Map
Meet the 150+ organizations that focus on machine learning applications with satellite data
Radiant Earth Foundation
Jan 20
SpatioTemporal Asset Catalogs and the Open Geospatial Consortium
SpatioTemporal Asset Catalogs and the Open Geospatial Consortium
As SpatioTemporal Asset Catalog (STAC) specification matures one of the more frequent questions we get asked is the relationship between…
Chris Holmes
Jan 19
Data Labeling Contest: Crowdsourcing a scalable solution to generate labels for satellite imagery
Data Labeling Contest: Crowdsourcing a scalable solution to generate labels for satellite imagery
A conversation with the First Place winners of the Data Labeling Contest
Radiant Earth Foundation
Jan 12
Can you guess if this place is real?
Can you guess if this place is real?
Generating synthetic training data that can improve the accuracy of machine learning models
Radiant Earth Foundation
Jan 12
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