Modeling Top-of-Atmosphere Anisotropic Reflectance of Discrete Forests Over Sloped Surface

Abstract

Characterizing the anisotropic features at the top of atmosphere (TOA) is crucial for vegetation monitoring and retrieval of biophysical parameters. The core challenge lies in modeling the mutual interactions between land surface and atmosphere, particularly in the context of rugged terrains and cloudy conditions. The GOSAILTA is proposed to extend the top-of-canopy (TOC) anisotropic reflectance geometric optical and mutual shadowing and scattering-from-arbitrarily-inclined-leaves model coupled with topography (GOSAILT) model to TOA reflectance/radiance by integrating Santa Barbara DISORT atmospheric radiative transfer (SBDART) model. The interactions between atmosphere and land surface are characterized for the effects of the sloped surface and its surrounding terrains under both clear and cloudy conditions. The model was validated against discrete anisotropic radiative transfer (DART) simulations, airborne observations from wide-angle infrared dual-model line/area array scanner (WIDAS), and satellite observations from HJ-1A/B constellation charge-coupled device (CCD). Results demonstrate high overall accuracy in the red band (coefficient of determination ( $R^{2}$ ) =0.993; root-mean-square error (RMSE) =0.008; and mean absolute percentage error (MAPE) =5.481%) and near-infrared (NIR) band ( $R^{2}=0.933$ , RMSE =0.025; and MAPE =6.227%) compared to DART simulations. The simulations show strong agreement with WIDAS and HJ, achieving an $R^{2}$ of 0.9. However, the accuracy is slightly lower for top-of-cloud reflectance, with an $R^{2}$ and MAPE of 0.311 and 14.972%, respectively, primarily due to limitations in cloud parameterization.