Physical Sciences and Mathematics Commons^™

The Role Of Topography, Soil, And Remotely Sensed Vegetation Condition Towards Predicting Crop Yield, Trenton E. Franz, Sayli Pokal, Justin P. Gibson, Yuzhen Zhou, Hamed Gholizadeh, Fatima Amor Tenorio, Daran Rudnick, Derek M. Heeren, Matthew F. Mccabe, Matteo Ziliani, Zhenong Jin, Kaiyu Guan, Ming Pan, John Gates, Brian Wardlow

School of Natural Resources: Faculty Publications

Foreknowledge of the spatiotemporal drivers of crop yield would provide a valuable source of information to optimize on-farm inputs and maximize profitability. In recent years, an abundance of spatial data providing information on soils, topography, and vegetation condition have become available from both proximal and remote sensing platforms. Given the wide range of data costs (between USD $0−50/ha), it is important to understand where often limited financial resources should be directed to optimize field production. Two key questions arise. First, will these data actually aid in better fine-resolution yield prediction to help optimize crop management and farm economics? Second, what …