Abstract
Anisotropic canopy reflectance plays a crucial role in estimating vegetation biophysical parameters, whereas soil reflectance anisotropy affects canopy reflectance. However, woodland canopy bidirectional reflectance distribution function (BRDF) models considering soil anisotropy are far from universal, especially for the BRDF models of mountain forest. In this study, a mountain forest canopy model, named geometric-optical and mutual shadowing and scattering from arbitrarily inclined-leaves model coupled with topography (GOSAILT), was extended to consider the soil anisotropic reflectance characteristics by introducing the simple soil directional (SSD) reflectance model. The modified GOSAILT model (named GOSAILT-SSD) was evaluated using unmanned aerial vehicle (UAV) field observations and discrete anisotropic radiative transfer (DART) simulations. Then, the effects of Lambertian soil assumption on simulating the vi-directional reflectance factor (BRF) were evaluated across different fractions of vegetation cover (Cv), view zenith angles (VZA), solar zenith angles (SZA), and spectral bands with the GOSAILT-SSD model. The evaluation results, with the DART simulations, show that the performance of the GOSAILT-SSD model in simulating canopy BRF is significantly improved, with decreasing RMSE, from 0.027 to 0.017 for the red band and 0.051 to 0.037 for the near-infrared (NIR) band. Meanwhile, the GOSAILT-SSD simulations show high consistency with UAV multi-angular observations (R2 = 0.97). Besides, it is also found that the BRF simulation errors caused by Lambertian soil assumption are too large to be neglected, with a maximum relative bias of about 45% for the red band. This inappropriate assumption results in a remarkable BRF underestimation near the hot spot direction and an obvious BRF overestimation for large VZA in the solar principal plane (PP). Meanwhile, this simulation bias decreases with the increase of fraction of vegetation cover. This study provides an effective technique to improve the capability of the mountain forest canopy BRDF model by considering the soil anisotropic characteristics for advancing the modeling of radiative transfer (RT) processes over rugged terrain.
Highlights
The results indicate that the Lambertian soil assumption can cause underestimation and overestimation of forest canopy bidirectional reflectance factor (BRF); the most serious underestimation occurs in the direction of hot spot effect, and the most serious overestimation occurs in the direction of forward-scattering
The anisotropy of soil reflectance is a significant source of uncertainty in BRF simulation of sparse woodland
The accuracy of the GOSAILT-simple soil directional (SSD) model was validated by employing unmanned aerial vehicle (UAV) field multi-angular observations and discrete anisotropic radiative transfer (DART) simulations
Summary
Anisotropic reflectance is a result of land surface intrinsic scattering properties, which, in turn, can be linked to its structural and biophysical characteristics, as described by the bidirectional reflectance distribution function (BRDF) [1,2]. BRDF is meaningful for scientific research and remote sensing applications, such as land cover classification, radiation budget, and vegetation dynamic monitoring [3,4]. Complex terrain, covering about 24% of the land surface of the Earth, significantly affects anisotropic reflectance by the modulation of local sun-terrain-sensor (STS) geometries and redistribution of the direct and diffuse radiations received by a target, which results in great challenges and complexities in BRDF modeling [5,6]. There have been increased interests in surface BRDF modeling over rugged
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