Physical interpretation of the correlation between multi-angle spectral data and canopy height

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Read Full Article (file size: 144279 bytes) Cited by GEOPHYSICAL RESEARCH LETTERS, VOL. 34, L18405, doi:10.1029/2007GL031143, 2007 Physical interpretation of the correlation between multi-angle spectral data and canopy height M. A. Schull Department of Geography and Environment, Boston University, Boston, Massachusetts, USA S. Ganguly Department of Geography and Environment, Boston University, Boston, Massachusetts, USA A. Samanta Department of Geography and Environment, Boston University, Boston, Massachusetts, USA D. Huang Atmospheric Sciences Division, Brookhaven National Laboratory, Upton, New York, USA N. V. Shabanov Department of Geography and Environment, Boston University, Boston, Massachusetts, USA J. P. Jenkins Complex System Research Center, University of New Hampshire, Durham, New Hampshire, USA J. C. Chiu Joint Center for Earth Systems Technology, University of Maryland, Baltimore County, Baltimore, Maryland, USA A. Marshak Climate and Radiation Branch, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA J. B. Blair Laser Remote Sensing Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA R. B. Myneni Department of Geography and Environment, Boston University, Boston, Massachusetts, USA Y. Knyazikhin Department of Geography and Environment, Boston University, Boston, Massachusetts, USA Abstract Recent empirical studies have shown that multi-angle spectral data can be useful for predicting canopy height, but the physical reason for this correlation was not understood. We follow the concept of canopy spectral invariants, specifically escape probability, to gain insight into the observed correlation. Airborne Multi-Angle Imaging Spectrometer (AirMISR) and airborne Laser Vegetation Imaging Sensor (LVIS) data acquired during a NASA Terrestrial Ecology Program aircraft campaign underlie our analysis. Two multivariate linear regression models were developed to estimate LVIS height measures from 28 AirMISR multi-angle spectral reflectances and from the spectrally invariant escape probability at 7 AirMISR view angles. Both models achieved nearly the same accuracy, suggesting that canopy spectral invariant theory can explain the observed correlation. We hypothesize that the escape probability is sensitive to the aspect ratio (crown diameter to crown height). The multi-angle spectral data alone therefore may not provide enough information to retrieve canopy height globally. Received 10 July 2007; accepted 22 August 2007; published 25 September 2007. Keywords: special invariants; canopy structure; multi-angle data. Index Terms: 0480 Biogeosciences: Remote sensing; 1631 Global Change: Land/atmosphere interactions (1218, 1843, 3322); 0428 Biogeosciences: Carbon cycling (4806); 1626 Global Change: Global climate models (3337, 4928); 0410 Biogeosciences: Biodiversity. Read Full Article (file size: 144279 bytes) Cited by Citation: Schull, M. A., et al. (2007), Physical interpretation of the correlation between multi-angle spectral data and canopy height, Geophys. Res. Lett., 34, L18405, doi:10.1029/2007GL031143. Copyright 2007 by the American Geophysical Union.

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