Machine learning for Earth Observation: Emissions, mitigation and sequestration

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Constellations of satellites such as the SENTINELs provide almost daily coverage of the earth using a variety of sensors: multispectral and hyperspectral images, synthetic aperture radar, LIDAR, etc. Recent advances in machine learning allow us to process these images at planet scale on a near real-time basis and to paint a very broad picture of key climate related topics such as greenhouse gas emissions, wildfire risk, flooding or carbon sequestration in forests. This talk will cover some of these examples in depth, illustrating some key open numerical challenge.

Speakers:

Alexandre d’Aspremont
Research Director, Co-founder
CNRS (Centre national de la recherche scientifique) & Kayrros
Moderator(s):

Gustau Camps-Valls
Professor in Electrical Engineering
Universitat de València

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The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.

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