Predicting and Preventing Crisis in Water and Food Security in a Changing Climate through a paradigm-shift in global cropland maps and products through machine learning and cloud computing
2021-10-01, 09:00–09:30, Group on Earth Observations

Adaptation and mitigation to climate change are key to ensuring global water and food security in the twenty-first century. In order to contribute to this humanity sustaining goal, the United States Geological Survey (USGS) produced the world’s first, Landsat Satellite-derived, global cropland extent product at 30m resolution (GCEP30) for the nominal year 2015 which is the highest resolution freely available global cropland dataset. The product was a result of a “paradigm-shift” in cropland production involving satellite sensor big-data analytics, machine learning, and cloud-computing on Google Earth Engine (GEE). The GCEP30 had an overall map accuracy of 91.7% with cropland class producer’s accuracy of 83.4% (errors of omission of 16.6%) and user’s accuracy of 78.3% (errors of commission of 21.7%). For the year 2015, GCEP30-derived global net cropland area was 1.873 Bha (~12.6% of the terrestrial area). The GCEP30 is downloadable at LP DAAC and viewable in full resolution here.

Talk, Sustainable Development
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Authors and Affiliations

United States Geological Survey (USGS)


Transition to FOSS4G


FOSS4G implementations in strategic application domains: land management, crisis/disaster response, smart cities, population mapping, climate change, ocean and marine monitoring, etc.


1 - Principiants. No required specific knowledge is needed.

Language of the Presentation