Abstract: Understanding Spatial Variability of Corn Yield Using Remotely Sensed Imagery. (ASA, CSSA and SSSA International Annual Meetings (2015))

82-1 Understanding Spatial Variability of Corn Yield Using Remotely Sensed Imagery.

See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Agricultural Remote Sensing: I

Monday, November 16, 2015: 1:00 PM

Minneapolis Convention Center, L100 GH

Bruno Basso¹, Benjamin Dumont², Greg Putman³, Jinshui Zhang², Jose E. Cora⁴ and Joe T. Ritchie⁵, (1)Michigan State University, Michigan State University, East Lansing, MI
(2)Geological Sciences, Michigan State University, East Lansing, MI
(3)Geological Sciences, Michigan State University, east Lansing, MI
(4)Depto de Solos, Sao Paulo State University, Jaboticabal, SP, BRAZIL
(5)Geological Sciences, Michigan State University, Belton, TX

Abstract:

The objective of this study is to illustrate the capability of remote sensing imagery to detect and understand spatial variability of corn yield across the US Midwest. Images were taken using UAV and planes using different sensors, and satellite. The images were able to detect yield differences, which then correlated with yield mapping results.

The timing of the images in the season showed to be an important factor when used to predict yield maps.

See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Agricultural Remote Sensing: I

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