Data from: 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
vegetation metrics from acquisitions with different flight patterns and
sensor parameters, we found that both flight altitude and pattern had
significant impacts on derived structure metrics, with variation in
altitude causing the largest impacts. Flying higher resulted in lower
point cloud heights, leading to a consistent downward trend in percentile
height metrics and fractional cover. The magnitude and direction of these
trends also varied depending on the vegetation type sampled (trees,
shrubs, or grasses), showing that the structure and composition of savanna
vegetation can interact with the lidar signal and alter derived metrics.
While there were statistically significant differences in metrics among
acquisitions, the average differences were often on the order of a few
centimeters or less, which shows great promise for future comparison
studies.We discuss how these results apply in practice, explaining the
potential trade-offs of flying at higher altitudes and alternating flight
pattern. We highlight how flight and sensor parameters can be geared
toward specific ecological applications and vegetation types, and we
explore future opportunities for optimizing UAV-lidar sampling designs in
savannas.