Developing remote sensing approaches for integrated pest and pollinator management in turfgrass

Golf courses can expand hundreds of acres, making scouting for both pests and beneficial insect populations a time-consuming task. Scouting for insects is labor-intensive, potentially damaging, but is an integral part of an integrated pest and pollinator management (IPPM) plan. Virginia golf courses are currently using remote sensing and light reflectance to detect non-insect pests in turfgrass. This thesis aims to develop remote sensing and light reflectance methods to aid in a turfgrass IPPM plan, to document the phenology of ABW weevil (Listronotus maculicollis Kirby, Coleoptera: Curculionidae, ABW), and to catalogue pollinator-friendly out-of-play areas. Light reflectance, the measurement of the amount of light reflected, of plants can be used as a proxy for the health of a plant. The light reflectance of turfgrass affected by ABW stress and plants in the out-of-play areas of golf courses was collected proximally and remotely, using a backpack spectrometer and an unmanned aerial vehicle (UAV), respectively. Mathematical light reflectance indices were applied and compared to insect populations in both areas to determine the correlation. The Normalized Difference Vegetation Index (NDVI), which uses red and near-infrared wavelengths to indicate stress, was found to highlight ABW stressed turfgrass. The Structure Intensive Vegetation Pigment Index (SIPI), which uses red and green wavelengths to highlight flowering plants, was found to highlight potential pollinator- friendly habitats in out-of-play areas. When applied to flights, NDVI could help in the targeted application of insecticides to combat the annual bluegrass weevil, therefore reducing their presence in the environment. The use of SIPI could highlight potential pollinator friendly habitats and therefore assist superintendents in the development of their IPPM plan.