Authors: Jacob Abramowitz*, Binghamton University, State University of New York, Andrey Petrov, Associate Professor, Department of Geography, University of Northern Iowa, Mark Sherrard, Associate Professor, Department of Biology, University of Northern Iowa
Topics: Agricultural Geography, Remote Sensing, Energy
Keywords: Hyperspectral, wind energy, agriculture
Session Type: Poster
Start / End Time: 1:10 PM / 2:50 PM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: Download
The number of wind turbines in Iowa is rapidly increasing. Many of these wind turbines are built on agricultural land, yet the effects they have on crop condition are poorly understood. If wind turbines affect crop condition, it could impact agriculture in the United States. Through calculation and comparison of four vegetation indices derived from hyperspectral data, this study sought to quantify this impact. Airborne hyperspectral data of corn and soybean fields in Story County, Iowa were collected, providing 332 bands between 398.35 – 1001.04 nm. Four vegetation indices (red-edge NDVI, green absorption NDVI, leaf area index, and photochemical reflectance index) were calculated in regions near the turbines, which were compared to control regions away from the turbines. In general, the presence of turbines negatively affected crop condition; however, the effect varied by crop type. Specifically, the presence of turbines tended to benefit corn crops but negatively impact soybean crops.