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Satellite Tree Enumeration Outside of Forests at the Fifty Centimeter Scale
Event Type
Invited Talk
Tags
Applications
Computational Science
Extreme Scale Computing
Machine Learning, Deep Learning and Artificial Intelligence
Registration Categories
TP
XO
TimeTuesday, 17 November 20201:45pm - 2:30pm EDT
LocationTrack 1
DescriptionA large proportion of trees grows isolated outside of forests and is not well documented. These non-forest trees play a crucial role in biodiversity, carbon storage, food resources and shelter for humans and animals. We have enumerated the crown size of individual trees greater than three square meters in a land area spanning ten million square kilometers from the Atlantic Ocean to the Red Sea in the West African Sahara, Sahel, in sub-humid zones using sub-meter satellite imagery, high-performance computing and deep learning. We enumerated over 14 billion isolated trees, or 140 trees/ha, with a median crown size of 12 square meters along a rainfall gradient from zero to 1000 mm. The canopy cover increases from near zero in hyper-arid zones to 9.9 trees/ha in the arid zone, to 30.1 trees/ha in the semi-arid Sahelian zone, to 470 trees/ha in the sub-humid zone. Although the overall tree cover is low, the unexpected higher density of isolated trees challenges prevailing narratives about dryland desertification, where even the desert showed a surprisingly higher tree density than previously thought. Our machine learning approach using high-performance computing enables enumeration of isolated trees globally to identify localized areas of degradation and to quantify the role of isolated trees in the global carbon cycle.
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