Within‐Season Calibration of Modeled Wheat Growth Using Remote Sensing and Field Sampling

Abstract

AbstractWithin‐season calibration using observations of growth and phenology provides an objective means for crop simulation models to be self‐correcting. Estimating crop growth and phenology for a large number of fields by traditional ground‐based sampling methods can be undesirably time‐consuming. Certain aspects of crop growth can be estimated more quickly for a large number of fields using remote sensing. A study was conducted to compare the results of calibrating a crop simulation model using within‐season observations of leaf area index (LAI) obtained either from field sampling or remote sensing. Winter wheat (Triticum aestivum L.) yields at three locations in the U.S. Great Plains for 2 yr were modeled more accurately using remotely sensed LAI observations, than using field‐sampled LAI observations. This difference in accuracy appeared to result from the apparent ability of the remotely sensed LAI observations to better represent the photosynthetically active plant area in the crop canopy. Results of the study indicate that remote sensing may be an effective source of field observations for within‐season calibration of crop simulation models.