Data envelopment analysis (DEA) has been applied to agricultural decision making units (DMU) such as individual farmers, groups of farmers, or other firms. Rather than firms as the DMU, each sub-field region within a farmer’s field can be evaluated as the DMU such that the efficiency of different management practices are evaluated. A hypothetical grid superimposed upon a field creates the DMU’s so that scale efficiency can be visually assessed in a map. Input variables include as-applied maps of inputs, geospatial data on soil characteristics, and remotely sensed imagery. Output variables are based upon yield monitor sensors from harvest equipment from one or more years and therefore one or more crops grown in rotation. Both bio-physical agronomic relationships and economic characteristics are evaluated. Based on our novel technique for evaluating geo-referenced technical efficiency scores, tests for global and local spatial autocorrelation indicate presence of spatial effects; thereby providing insights into natural versus man-made variability.