Proximal and Unmanned Aerial Remote Sensing for Monitoring Crop Growth and Stress

As pressure on available water resources increases, technology should be leveraged to increase crop water use efficiency. Research heretofore rarely addresses the use of multispectral UAV imagery in cotton irrigation management. The objective of this study was to determine whether multispectral UAV imagery or vector proximal data could quantify in-field variability in irrigated cotton production. This study comprised a randomized split plot design with four replications. The main plot factor was three irrigation rates applied as a percentage of the estimated evapotranspiration (ET) requirement (0, 40, and 80 %) and the sub-plot factor was eight cultivars. Multispectral UAV imagery was acquired at weekly intervals from 30 m altitude. Proximal data was collected from a high clearance rover with boom-mounted sensors. Weekly data was analyzed to assess whether data from either platform was representative of crop growth (e.g. yield and plant height) and stress conditions at several growth stages. Detailed results from this study will be presented at the meeting.