Integrating Crop Models and Precision Agriculture Technologies to Understand Spatial and Temporal Variability of Crop Yield.

Big-data from sensors in agriculture along with recent advancements in the geospatial and computational modeling sciences provide new opportunities to improve the environmental sustainability and efficiency of agriculture to meet the food, feed, fiber and fuel needs for the growing global population. Crop models have the capacity to quantify the dynamic feedback between soil, climate, genetics and management under current and future climate scenarios.

The paper describes the critical role that crop models have to better understand spatial and temporal variation of crop yields across different spatial scales, ranging from within-field to regions. Different case studies on the integration between yield map technologies, remote sensing and crop models will be presented.