Flying high: Sampling savanna vegetation with UAV-lidar

The flexibility of UAV-lidar remote sensing offers a myriad of new opportunities for savanna ecology, enabling researchers to measure vegetation structure at a variety of temporal and spatial scales. However, this flexibility also increases the number of customizable variables, such as flight altitude, pattern, and sensor parameters, that, when adjusted, can impact data quality as well as the applicability of a dataset to a specific research interest. To better understand the impacts that UAV flight patterns and sensor parameters have on vegetation metrics, we compared 7 lidar point clouds collected with a Riegl VUX-1LR over a 300 x 300 m area in the Kruger National Park, South Africa. We varied the altitude (60 m above ground, 100 m, 180 m, and 300 m) and sampling pattern (slowing the flight speed, increasing the overlap between flightlines, and flying a crosshatch pattern), and compared a variety of vertical vegetation metrics related to height and fractional cover. Comparing vegetati..., , The point cloud files (LAS files) were denoised and classified (Default: Class 1, Ground: 2, Noise: 7, HighScanAngles: 10) using the Terrasolid software suite. The point clouds can be input into the VoxelMetrics pipeline in Lidar-Notebooks (https://github.com/pbb2291/Lidar-Notebooks) to recreate all of the metrics reported in Boucher et al. (2023; Flying High: Sampling Savanna Vegetation with UAV-lidar). The CHM and DTM raster files (GeoTIFF files) used in Boucher et al. (2023) are also available for download.