Integration of Ground- and UAS-Platforms for the Evaluation of Cultivar Performance (phenotyping) and Experimental Treatments

The purpose of this project is to identify best performing genotypes or experimental treatments cotton research plots using ground- and UAS based remote sensing platforms.   Sensors used in this ground-based platform include an ultrasonic sensor used to determine plant height and a multi-spectral sensor used to estimate Normalized Difference Vegetation Index (NDVI) and an infrared sensor used to measure canopy temperature.  Plant height is an important component of canopy cover and interception of solar radiation. NDVI is a parameter that takes into account the reflectance of infrared (~ 0.87 mm) and red (~ 0.65 mm) wavelength by plants.  Healthy vegetation reflects very well in the near-infrared part of the electromagnetic spectrum. Canopy temperature is an important indicator of the current water status of plants. The UAS platform is equipped with multiple sensors that can capture images in 4 spectral bands (Blue, Green, Red, and NIR).  Images acquired from the UAS are processed using Structure from Motion (SfM) algorithm to generate fine spatial resolution orthomosaic images and dense 3D point cloud data. These geospatial data products provided valuable information on two-dimensional canopy cover and three-dimensional vertical profiles of plants, so that these measurements can be used to track growth rates of plant height and crop volume over the season at spatial and temporal scales that have not been possible via traditional remote sensing methods.