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Invasive species detection in Hawaiian rainforests using airborne imaging spectroscopy and LiDAR
Authors:Gregory P Asner  David E Knapp  Ty Kennedy-Bowdoin  Matthew O Jones  Roberta E Martin  Joseph Boardman  R Flint Hughes
Affiliation:

aDepartment of Global Ecology, Carnegie Institution, 260 Panama Street, Stanford, CA 94305, USA

bAnalytical Imaging and Geophysics LLC, Boulder, CO 80302, USA

cInstitute of Pacific Islands Forestry, USDA Forest Service, Hilo, HI 96720, USA

Abstract:Remote sensing of invasive species is a critical component of conservation and management efforts, but reliable methods for the detection of invaders have not been widely established. In Hawaiian forests, we recently found that invasive trees often have hyperspectral signatures unique from that of native trees, but mapping based on spectral reflectance properties alone is confounded by issues of canopy senescence and mortality, intra- and inter-canopy gaps and shadowing, and terrain variability. We deployed a new hybrid airborne system combining the Carnegie Airborne Observatory (CAO) small-footprint light detection and ranging (LiDAR) system with the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) to map the three-dimensional spectral and structural properties of Hawaiian forests. The CAO-AVIRIS systems and data were fully integrated using in-flight and post-flight fusion techniques, facilitating an analysis of forest canopy properties to determine the presence and abundance of three highly invasive tree species in Hawaiian rainforests.

The LiDAR sub-system was used to model forest canopy height and top-of-canopy surfaces; these structural data allowed for automated masking of forest gaps, intra- and inter-canopy shadows, and minimum vegetation height in the AVIRIS images. The remaining sunlit canopy spectra were analyzed using spatially-constrained spectral mixture analysis. The results of the combined LiDAR-spectroscopic analysis highlighted the location and fractional abundance of each invasive tree species throughout the rainforest sites. Field validation studies demonstrated < 6.8% and < 18.6% error rates in the detection of invasive tree species at not, vert, similar 7 m2 and not, vert, similar 2 m2 minimum canopy cover thresholds. Our results show that full integration of imaging spectroscopy and LiDAR measurements provides enormous flexibility and analytical potential for studies of terrestrial ecosystems and the species contained within them.

Keywords:Airborne Visible and Infrared Imaging Spectrometer  AVIRIS  Carnegie Airborne Observatory  CAO  Hawaii  Invasive species  Light detection and ranging  Tropical forest
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