UAV lidar and hyperspectral fusion for forest monitoring in the southwestern USA

Temuulen Sankey, Jonathon Donager, Jason McVay, Joel B. Sankey

Research output: Contribution to journalArticlepeer-review

256 Scopus citations

Abstract

Forest vegetation classification and structure measurements are fundamental steps for planning, monitoring, and evaluating large-scale forest changes including restoration treatments. High spatial and spectral resolution remote sensing data are critically needed to classify vegetation and measure their 3-dimensional (3D) canopy structure at the level of individual species. Here we test high-resolution lidar, hyperspectral, and multispectral data collected from unmanned aerial vehicles (UAV) and demonstrate a lidar-hyperspectral image fusion method in treated and control forests with varying tree density and canopy cover as well as in an ecotone environment to represent a gradient of vegetation and topography in northern Arizona, U.S.A. The fusion performs better (88% overall accuracy) than either data type alone, particularly for species with similar spectral signatures, but different canopy sizes. The lidar data provides estimates of individual tree height (R2 = 0.90; RMSE = 2.3 m) and crown diameter (R2 = 0.72; RMSE = 0.71 m) as well as total tree canopy cover (R2 = 0.87; RMSE = 9.5%) and tree density (R2 = 0.77; RMSE = 0.69 trees/cell) in 10 m cells across thin only, burn only, thin-and-burn, and control treatments, where tree cover and density ranged between 22 and 50% and 1–3.5 trees/cell, respectively. The lidar data also produces highly accurate digital elevation model (DEM) (R2 = 0.92; RMSE = 0.75 m). In comparison, 3D data derived from the multispectral data via structure-from-motion produced lower correlations with field-measured variables, especially in dense and structurally complex forests. The lidar, hyperspectral, and multispectral sensors, and the methods demonstrated here can be widely applied across a gradient of vegetation and topography for monitoring landscapes undergoing large-scale changes such as the forests in the southwestern U.S.A.

Original languageEnglish (US)
Pages (from-to)30-43
Number of pages14
JournalRemote Sensing of Environment
Volume195
DOIs
StatePublished - Jun 15 2017

Keywords

  • 3D modelling
  • Airborne data
  • Crown diameter
  • DEM
  • Drone
  • Structure from motion (SFM)
  • Tree delineation
  • UAS

ASJC Scopus subject areas

  • Soil Science
  • Geology
  • Computers in Earth Sciences

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