SPECTRAL INPUTS TO CROP IDENTIFICATION AND CONDITION ASSESSMENT

From an agronomic perspective, contemporary remote sensing research on crop identification and condition assessment is discussed. The basic relationships of reflectance and biophysical properties of crop canopies are first reviewed. Leaf area index is shown to be a key parameter linking multispectral reflectance and crop physiology. Major advancements in capability, particularly the development of spectral-temporal profile models, for crop identification have been made in the past decade. The same model form has been used for estimating crop development stage, leaf area index, and canopy light interception as inputs to crop growth and yield models. Potential advancements in capability with respect to new sensors are also discussed.