In grazed dairy pastures, the largest N source for both nitrate (NO3-) leaching and nitrous oxide (N2O) emissions is urine-N excreted by the animals. Additional application of N on urine patches as fertilizer may increase these losses so adapting N-fertilisation in these areas is necessary. The objective of this study was to examine the use of a tractor mounted LiDAR (Light Detection and Ranging) system to accurately identify and quantify areas affect by excess N, such as urine and dung. To do so, a controlled experiment was designed in a paddock with no recent exposure to animals or N fertilisation. Synthetic urine was randomly applied within two 20m x 20m blocks and weekly LiDAR scans were taken for 5 weeks. LiDAR based contour maps of the pasture canopy were shown to accurately detect the asymmetric urine patches as well as calculate a percent area of urine based high N as early as one week after a simulated grazing event. Further, weekly flights were taken with a remotely piloted aircraft system (RPAS/UAV) to have aerial footage of the trial. Resulting mosaic of RGB and NIR images were used to create photogrammetric based contour maps. Both approaches (LiDAR and photogrammetry) show no significant difference in the identification and sizing of urine patch cluster
