UAV hyperspectral and lidar data and their fusion for arid and semi-arid land vegetation monitoring

Temuulen T. Sankey, Jason McVay, Tyson L. Swetnam, Mitchel P. McClaran, Philip Heilman, Mary Nichols

Research output: Contribution to journalArticle

38 Scopus citations

Abstract

Unmanned aerial vehicles (UAVs) provide a new research tool to obtain high spatial and temporal resolution imagery at a reduced cost. Rapid advances in miniature sensor technology are leading to greater potentials for ecological research. We demonstrate one of the first applications of UAV lidar and hyperspectral imagery and a fusion method for individual plant species identification and 3D characterization at submeter scales in south-eastern Arizona, USA. The UAV lidar scanner characterized the individual vegetation canopy structure and bare ground elevation, whereas the hyperspectral sensor provided species-specific spectral signatures for the dominant and target species at our study area in leaf-on condition. We hypothesized that the fusion of the two different data sources would perform better than either data type alone in the arid and semi-arid ecosystems with sparse vegetation. The fusion approach provides 84–89% overall accuracy (kappa values of 0.80–0.86) in target species classification at the canopy scale, leveraging a wide range of target spectral responses in the hyperspectral data and a high point density (50 points/m2) in the lidar data. In comparison, the hyperspectral image classification alone produced 72–76% overall accuracies (kappa values of 0.70 and 0.71). The UAV lidar-derived digital elevation model (DEM) is also strongly correlated with manned airborne lidar-derived DEM (R2= 0.98 and 0.96), but was obtained at a lower cost. The lidar and hyperspectral data as well as the fusion method demonstrated here can be widely applied across a gradient of vegetation and topography to monitor and detect ecological changes at a local scale.

Original languageEnglish (US)
Pages (from-to)20-33
Number of pages14
JournalRemote Sensing in Ecology and Conservation
Volume4
Issue number1
DOIs
StatePublished - Mar 2018

Keywords

  • 3D modeling
  • UAV
  • high-resolution DEM
  • lidar
  • species identification
  • vegetation monitoring

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Computers in Earth Sciences
  • Nature and Landscape Conservation

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