Gp. Asner et al., UNMIXING THE DIRECTIONAL REFLECTANCES OF AVHRR SUB-PIXEL LANDCOVERS, IEEE transactions on geoscience and remote sensing, 35(4), 1997, pp. 868-878
Recent progress in canopy bidirectional reflectance distribution funct
ion (BRDF) model inversions has allowed accurate estimates of vegetati
on biophysical characteristics from remotely sensed multi-angle optica
l data, Since most current BRDF inversion methods utilize one-dimensio
nal (1-D) models, surface homogeneity within an image pixel is implied
, The Advanced Very High Resolution Radiometer (AVHRR) is one of the f
ew spaceborne sensors capable of acquiring radiometric data over the r
ange of view angles required for BRDF inversions. However, its relativ
ely coarse spatial resolution often results in measurements of mixed l
andcovers, and thus the data may not be ideal for BRDF inversions, We
present a three-step spectral unmixing method for retrieving AVHRR sub
-pixel directional reflectances in regions of high spatial heterogenei
ty. The reflectances of individual vegetation types are deconvolved us
ing co-located Landsat TM and AVHRR data. The three major steps in the
model include: 1) unmixing of vegetation endmember concentrations in
TM imagery; 2) correction of dissimilar shadow fractions between TM an
d AVHRR data; and 3) unmixing of AVHRR sub-pixel reflectances of veget
ation types for any sun-sensor geometry, We tested the method using si
mulated TM and AVHRR data. A savanna landscape simulation, comprised o
f a canopy radiative transfer model and a crown geometric-optical mode
l, was used to create images containing mixed pixels of tree, grass, a
nd shade endmembers. TM and AVHRR spectral response functions, viewing
geometries, and off-nadir pixel shape calculations were incorporated
into the simulations, Following the successful testing of the unmixing
method on error-free simulations, random noise representing atmospher
ic perturbations and co-registration inaccuracies was added to the dat
a. The method Is stable when errors resulting from either the first un
mixing step or image co-registration inaccuracies are introduced, Pote
ntial errors in the AVHRR data may result in inaccurately retrieved re
flectances if the image scene contains a spatially homogeneous mix of
landcovers. A method for detecting and mitigating this problem is pres
ented.