Ground-based and aerial remote sensing methods for estimating cotton growth, water stress, and defoliation
Ritchie, Glen Lorin
MetadataShow full item record
Remote sensing of visible and near-infrared crop reflectance has been closely tied to crop growth and health. The purpose of this research was to extend the application of remote sensing for irrigation and defoliation management of cotton (Gossypium hirsutum L.). Leaf area index of cotton subjected to defoliation treatments was regressed against normalized indices of visible and near-infrared reflectance. It was determined that combinations of red edge and near-infrared reflectance most accurately estimate leaf area index. A camera system comprising off-the-shelf digital cameras was tested as a means of collecting visible and near-infrared reflectance data throughout the growing season and a correction factor for exposure value was derived to allow estimates of relative reflectance. Vegetation indices based on camera and spectrometer reflectance measurements were compared with crop ground cover over three seasons and found to be sensitive to changes in ground cover within a limited ground cover range. Irrigation treatments based on changes in ground cover and vegetation index values were found to use less water and have yields comparable to treatments irrigated based on soil tension measurements.