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

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Schull, M., Ganguly, S., Samanta, A., Huang, D., Shabanov, N., Jenkins, J., Chiu, C., Marshak, A., Blair, J., Myneni, R. and Knyazikhin, Y. (2007) Physical interpretation of the correlation between multi-angle spectral data and canopy height. Geophysical Research Letters, 34 (18). L18405. ISSN 0094-8276

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To link to this article DOI: 10.1029/2007GL031143

Abstract/Summary

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.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > Department of Meteorology
ID Code:16766
Publisher:American Geophysical Union

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