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

By Yonah Bromberg Gaber, Geospatial Data Specialist, Radiant Earth Foundation

Machine learning (ML) applications for Earth observation (EO) can use currently available data that are collected via surveys for empirical research to investigate applied sciences or conduct socio-economic…

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Helping the global development community navigate the Machine Learning and Earth observation marketplace and innovations taking place.

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Radiant Earth Foundation

Radiant Earth Foundation

A non-profit on a mission to make insights from Earth observations and machine learning more accessible for global development organizations and communities.

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