A mixture modeling approach to estimate vegetation parameters for heterogeneous canopies in remote sensing

In this article, we describe a reflectance model which parametrizes the ref lectance of vegetation canopies from optical properties of leaves and soil, and dominant canopy structural parameters. The model assumes certain princ iples of geometric models, for example, that sensor integrates the radiance reflected from three components, plant, shaded soil, and illuminated soil. Its inversion provides compositional information of the ground surface tha t is linked with the interpretation of the linear spectral mixture modeling (LSMM). This model also offers the potential for retrieving other meaningf ul biophysical properties such as LAI. The model has been tested on simulat ed spectra of spectral mixtures in presence of significant multiple scatter ing. Results indicate that this modeling approach is a suitable remote sens ing tool for retrieving the vegetation abundance in heterogeneous canopies, which is interpreted as the fractional cover of plants with well-defined s tructural parameters. (C) Elsevier Science Inc., 2000.