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Proceedings Paper

Fusing waveform lidar and hyperspectral data for species-level structural assessment in savanna ecosystems
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Paper Abstract

Research groups at Rochester Institute of Technology and Carnegie Institution for Science are studying savanna ecosystems and are using data from the Carnegie Airborne Observatory (CAO), which integrates advanced imaging spectroscopy and waveform light detection and ranging (wLIDAR) data. This component of the larger ecosystem project has as a goal the fusion of imaging spectroscopy and wLIDAR data in order to improve per-species structural parameter estimation. Waveform LIDAR has proven useful for extracting high vertical resolution structural parameters, while imaging spectroscopy is a well-established tool for species classification. We evaluated data fusion at the feature level, using a stepwise discrimination analysis (SDA) approach with feature metrics from both hyperspectral imagery (HSI) and wLIDAR data. It was found that fusing data with the SDA improved classification, although not significantly. The principal component analysis (PCA) provided many useful bands for the SDA selection, both from HSI and wLIDAR. The overall classification accuracy was 68% for wLIDAR, 59% for HSI, and 72% for the fused data set. The kappa accuracy achieved with wLIDAR was 0.49, 0.36 for HSI, and 0.56 for both modalities.

Paper Details

Date Published: 29 April 2010
PDF: 10 pages
Proc. SPIE 7684, Laser Radar Technology and Applications XV, 76841H (29 April 2010); doi: 10.1117/12.849882
Show Author Affiliations
Diane Sarrazin, Rochester Institute of Technology (United States)
Jan van Aardt, Rochester Institute of Technology (United States)
Gregory P. Asner, Carnegie Institution for Science (United States)
Joe McGlinchy, Rochester Institute of Technology (United States)
David W. Messinger, Rochester Institute of Technology (United States)
Jiaying Wu, Rochester Institute of Technology (United States)


Published in SPIE Proceedings Vol. 7684:
Laser Radar Technology and Applications XV
Monte D. Turner; Gary W. Kamerman, Editor(s)

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