Research
David Helman's Modeling and Monitoring Vegetation Systems (M&M-VS) Lab focuses on better understanding soil-plant-air processes as well as environmental aspects of vegetation dynamics through the use of modeling (numerical simulations) and monitoring with proximal and remote (drones and satellites) sensing.
We use advanced techniques (time series analysis, machine learning, etc.) to interpret simulations (from numerical models) and observations (from satellites, drones, ground sensors, as well as other platforms).
We not only want to understand how climatic, environmental and human factors affect agricultural and natural vegetation systems but also aim to provide farmers with practical tools to improve agricultural practices so they can gain more (agricultural productivity) with less (resources)... Among our interests:
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