107 Comparison of Vegetative Indices Using an Unmanned Aerial Vehicle (UAV) and Satellite Imagery in Heifers Grazing Annual Ryegrass

Abstract Grazing management is heading towards a more digitized world where producers can use technology such as satellite imagery, drone imagery and global positioning system (GPS) data sets for matching real-time forage availability to livestock nutritional needs. The objective of this study was to compare vegetative indices between unmanned aerial vehicles (UAV) and satellite imagery to observe changes in forage mass in relation to environment and grazing pressure. This project took place at the H. H. Leveck Animal Research Center located in Starkville, MS where nine, two-hectare pastures planted in Marshall annual ryegrass (Lolium multiflorum) were utilized. Each pasture was monitored with a satellite and UAV over a 76-day grazing period with images taken every 14-days. Images from the UAV were captured at 121.9 m above ground level using a DJI inspire 2 rotor wing fitted with a MicaSense RedEdge camera (MicaSense®; Seattle,WA). Satellite images were captured using a constellation of satellites from Planet (Plant Labs Inc.; San Francisco, CA). Images were processed using Pix4D (Pix4D SA; Prilly, Switzerland) and analyzed in ArcGIS (ArcGIS; Esri; Redlands, CA). Normalized vegetation index (NDVI) was calculated for both imagery platforms. In addition, forage samples were collected for future analysis every 14-days to calculate biomass and observe forage nutritive value. Each UAV image was resampled using cubic convolution to match spatial resolution of the satellite image. Raster calculator in ArcGIS was utilized to calculate NDVI values between images. Reported NDVI value data were analyzed in the NPAR1WAY procedure of SAS® software, Version 9.4 (SAS Institute, Cary, NC, 2013). using a significance level of α = 0.05. Greenness of vegetation was significantly greater (P< 0.0001) for the UAV compared to the satellite imagery with NDVI being 0.80 compared to 0.78 respectively. In conclusion, vegetation observed by UAV imagery reports greater density of green vegetation.