Modeling Top-of-Atmosphere Anisotropic Reflectance of Discrete Forests Over Sloped Surface
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 Wideangle 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 (R2) = 0.993; root-mean-square error (RMSE) = 0.008; mean absolute percentage error (MAPE) = 5.481%) and near-infrared (NIR) band (R2 = 0.933, RMSE = 0.025; MAPE = 6.227%) compared to DART simulations. The simulations show strong agreement with WIDAS and HJ, achieving an R² of 0.9. However, the accuracy is slightly lower for top-of-cloud reflectance, with an R² and MAPE of 0.311 and 14.972%, respectively, primarily due to limitations in cloud parameterization.
Authors
- Yuan Han (ORCID: https://orcid.org/0000-0002-3542-9590)
- Qinhuo Liu (ORCID: https://orcid.org/0000-0002-3713-9511)
- Dongqin You (ORCID: https://orcid.org/0000-0002-5678-1307)
- Huaijing Wang (ORCID: https://orcid.org/0000-0001-5415-1208)
- Congcong Zhao
- Jianguang Wen (ORCID: https://orcid.org/0000-0002-1060-1817)
- Yong Tang (ORCID: https://orcid.org/0009-0004-5742-2981)
- Guokai Liu
- Kexin Wei
Institutions
- Aerospace Information Research Institute (CN)
- State Key Laboratory of Remote Sensing Science (CN)
Publication Details
- Journal
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tgrs.2025.3557557
- Citations
- 2
- Primary Topic
- Remote Sensing and LiDAR Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.60