Estimating Downward Shortwave Radiation over Complex Terrain: Synergizing Sentinel-2 Imagery and Topographic Data via Physics-Guided XGBoost
Year: 2026
Type: article
Abstract: Downward shortwave radiation (DSR) varies strongly across mountain slopes, and products designed for horizontal surfaces may not resolve this variability. We estimated slope-parallel DSR at eight Saihanba sites using Sentinel-2 imagery, topography, atmospheric inputs, and BRDF-informed surface albedo. Both branches used XGBoost, with the clear-sky branch further incorporating a parameterized radiation anchor, bounded residual learning, and support-aware output correction. On the 2024 test set (n = 1451), the full framework achieved an RMSE of 92.60 W/m2, an NRMSE of 15.79% and an R2 of 0.897. Pooled leave-one-site-out validation across all 6096 samples yielded an RMSE of 113.68 W/m2. For horizontal-surface observations at 10 Heihe River Basin stations, NRMSE was 17.60%. Clear-sky estimates depended most on solar-incidence geometry, whereas top-of-atmosphere spectra dominated the cloudy-sky XGBoost model.
Source: Remote Sensing
DOI: 10.3390/rs18203483
Institution: Liaocheng University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $3,258
Awards: G9001172077, G9001176092
OpenAlex ID: W7221505249
