F. Gao et al., Using a multikernel least-variance approach to retrieve and evaluate albedo from limited bidirectional measurements, REMOT SEN E, 76(1), 2001, pp. 57-66
When a multikernel modelling approach is being applied to remotely sensed d
ata, a new criteria - least variance of white-sky albedo selects semiempiri
cal bidirectional reflectance distribution function (BRDF) kernel combinati
ons better than the more conventional least-squares fitting criteria. The B
RDF describes the scattering of light from surface as a function of illumin
ation and view geometry. Semiempirical kernels are nonlinear geometric func
tions derived from a simplification of physical models of scattering. These
are combined linearly to fit observed bidirectional reflectance measuremen
ts. White-sky albedo (bihemispherical reflectance) is the integral of direc
tional reflectance for all viewing and illumination directions and is a tru
e surface property. The variance of retrieved white-sky albedo is a functio
n of the noises of measurement, the specific viewing and illumination geome
try of the surface scattering measurements, and the number of observations
used in the inversion. By selecting the kernel combination that provides th
e least variance of white-sky albedo, our studies show that a more stable e
stimate of white-sky and black-sky (directional-hemispherical) albedo is pr
oduced. (C) 2001 Elsevier Science Inc. All lights reserved.