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Journal Article

Variability in leaf and litter optical properties: implications for BRDF model inversions using AVHRR, MODIS, and MISR

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Asner, G. P., Wessman, C. A., Schimel, D. S., & Archer, S. (1998). Variability in leaf and litter optical properties: implications for BRDF model inversions using AVHRR, MODIS, and MISR. Remote Sensing of Environment, 63(3), 243-257.

Cite as: https://hdl.handle.net/11858/00-001M-0000-000E-E0CA-6
Canopy radiative transfer models simulate the bidirectional reflectance distribution function (BRDF) of vegetation covers with differing leaf and soil spectral and canopy structural characteristics. Numerical inversion of these models has provided estimates of vegetation structural and biophysical characteristics from multiangle, remotely sensed optical data. The number of angularly unique observations compared to BRDF model parameters largely determines the accuracy of retrievals. To increase this ratio, additional observations of a target must be acquired and the BRDF models and inversions must be simplified. The former will occur when the EOS instruments become available. Previous studies suggest that simplification of BRDF model inversions may best be accomplished by constraining the leaf optical parameters. This study focused on full-range (400-2500 nm) leaf and litter spectral properties convolved to ASHRR, MODIS, and MISR optical channels. Using a diverse array of woody plant and grass species, we found robust and readily usable interrelationships among spectra through correlation, regression and principal components analyses. Significant differences between green leaf and litter optical properties and their sensor specific interrelationships indicate that green leaf optical constraints may be useful with BRDF retrievals to detect the onset of canopy senescence. These findings will provide increased efficiency in canopy BRDF model inversions by decreasing the number of observations required to retrieve canopy structural and biophysical information from multiangle remotely sensed data. (C) Elsevier Science Inc., 1998. [References: 44]