Automated Change Detection: A Solution for ESA Monitoring

Automated Change Detection: A Solution for ESA Monitoring

As we move into winter in the Northern Hemisphere and the days shorten and the temperature drops, your thoughts might turn to warmer, sunnier places. Ah, yes, a place like Puerto Rico! Tropical breezes, wonderful beaches, and—at the fore of our mind—turtlefat (Auerodendron pauciflorum)! This cool little plant from the northern part of the island is highly endangered, with just a couple dozen individuals known to exist over some 200,000 acres. It is protected under the Endangered Species Act (ESA), and part of that protection means monitoring the places it lives so we know how the species and its habitat are faring. This is easier said than done: how can we monitor habitat for turtlefat or the hundreds of other ESA-listed species threatened by habitat loss, in the face of limited budgets for our wildlife agencies? Fortunately, advances in technology provide one solution in the form of machine learning and satellite imagery. Learn more here!

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Sarina Weiss
2019 Fall Intern in Geoinformatics