Modeling the reflectance anisotropy of Chihuahuan Desert grass-shrub transition canopy-soil complexes

The goal of the research presented here is to understand better the factors controlling the remotely sensed signal returned in the solar wavelengths from Chihuahuan Desert grass-shrub transition canopy-soil complexes. The specific objectives were twofold: to evaluate the importance of the different elements (overstory, understory, soil) in the bi-directional reflectance distribution function (BRDF) of a Chihuahuan Desert grass-shrub transition zone; and to explore the behavior of simple parametric and explicit scattering models with respect to observations. The first objective was approached by simulations using the Radiosity Graphics Method (RGM) radiosity package, with surface parameters provided by measurements of plant locations and dimensions surveyed over 25 m2 plots. The second was approached through simulations of bidirectional reflectance factors (BRFs) by both the RGM and a Simplified Geometric Model (SGM) developed for inversion purposes (Chopping et al 2002). The simulated reflectance values were assessed against samples of the BRDF at a wavelength of 650 nm acquired from the air at six view zenith angles and three solar zenith angles by tilting a radiometrically-calibrated digital camera (providing multi-angle observations, MAO). The results show that the understory of small forbs and sub-shrubs plays a very important role in determining the brightness and -to a lesser extent -reflectance anisotropy of grass-shrub transition landscapes, in relation to that of larger shrubs such as mesquite and ephedra: removing snakeweed from the simulations resulted in considerably higher BRF values This is owing to the potential large number density of these plants and to the fact that there is also a varying proportion of black grama grass and prone grass litter, here associated with snakeweed abundance. Both of these components darken the scene. The SGM performed well measured against both the RGM and the MAO (r2 of 0.98 and 0.92 against the RGM output and MAO, respectively). Both models underestimated BRF magnitude by a small amount, less than 6%, with both showing increasing divergence from the backcsattering into the forward-scattering direction. A remaining problem for operational model inversions using MAO is the a priori estimation of understory and grass abundance.