Integrating Remote Sensing To Improve Crop Grain Yield Estimates For Assessing Within Field Spatial And Temporal Variability

accuracy than LR models, and the models were able to explain up to 83% within-field yield variability. Model based yield maps demonstrated within-field yield differences better than yield monitor data. Spatial variability of crop yield was generally lower than temporal variability. Topographic properties were found to play significant role in within-field yield differences. Areas with lower slope were found to have higher yield suggesting the need to consider topographic variabilities in implementation of agricultural practices. Improved understanding on processes underlying spatial and temporal variability of crop yield can help develop management practices for optimal productivity with improved environmental quality.