Directed sampling using remote sensing with a response surface sampling design for site-specific agriculture

Abstract

Remotely sensed imagery provides contiguous spatial coverage of a field and can be used as a surrogate to measure crop and soil attributes. Empirical regression models are often used to convert imagery to attribute maps, when an a priori linear relationship can be assumed to exist between the imagery and ground attributes. In this study, we used the response surface approach incorporated in the ECe Sampling, Assessment, and Prediction (ESAP) software to create ground sampling designs from input imagery in order to develop regression equations for predicting crop height and width attributes in a 3.4-ha cotton field. We examined both the reliability of this model-based sampling approach as wel..