Estimating health of hybrid bermudagrass managed by soil moisture sensors using remote sensing technology

The application of modern technologies such as soil moisture sensors (SMS) provide an excellent water management and conservation tool, which reduces daily water use. The overall goal of this project is to employ UAV-based remote sensing technology to estimate bermudagrass performance and quality managed under SMS and ET based irrigation at Cal Poly Pomona's Turfgrass Center. In addition to the UAV-based remote sensing technology, hand-held spectroradiometer and chlorophyll meter were also used to determine Bermudagrass performance. Data was collected from a UAV equipped with a multispectral sensor along with visual quality ratings and proximal sensor data. General linear model of correlation (p = 0.05) was used to analyze percentage green cover, density, NDVI, and other vegetation indices