Keelin Haynes graduated from Miami University of Ohio with a Bachelor of Arts in Political Science and a minor in Middle Eastern and Islamic Studies, before continuing on to receive a Master of Arts in Geography. His graduate studies focused on remote sensing applications in agricultural monitoring and wildfire modeling, machine learning classification, and open source GIS methodologies. His thesis focused on predictive land-cover/ land-use change modeling in southwest Vietnam, specifically on how economic, cultural, and policy decisions can drive crop conversion in the Mekong Delta.

Before joining Harvest, Keelin worked on projects including scenario driven landscape modeling for NASA’s Land-Cover/ Land-Use Change Program, arctic wildfire modeling in Greenland, and the analysis of remotely-sensed fire data for a NOAA/NASA FIREX-AQ field campaign.

CV:
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Email
haynesk [at] umd.edu