A multi-scale assessment of topographic anisotropy on Land Surface Emissivity and Temperature retrieval over the Yarlung Tsangpo River basin

Accurate Land Surface Temperature (LST) retrieval is critical for monitoring cryospheric and hydrological processes, yet standard algorithms often fail in rugged terrain by neglecting directional Land Surface Emissivity (LSE) effects. This study quantified the impact of terrain-induced LSE anisotropy on LST estimation across the topographically complex Yarlung Tsangpo River Basin (YTRB). We integrated multi-source remote sensing data with an empirical directional emissivity model and a generalized single-channel LST algorithm, explicitly evaluating the sensitivity of the topographic correction to the LSE/LST spatial scale and Digital Elevation Model (DEM) fidelity. Results reveal a strong scale dependence: while terrain-induced biases are negligible at coarse scales (~5 km), they become substantial at finer resolutions. At a 250 m resolution, LSE biases on steep slopes (>50°), which represent critical areas for cryospheric dynamics, reached ~0.02, propagating into LST errors exceeding 1.5 K. Crucially, the fidelity of the input DEM governs the magnitude of the correction. Our sensitivity analysis revealed that emissivity adjustments derived from a high-resolution (30 m) DEM were 2–3 times greater in magnitude than those derived from a coarser DEM (1 km) on moderate slopes (30°–50°). Quantitative analysis further demonstrates that topographic correction effectively eliminates the pseudo-correlation between emissivity and slope (R2 reduced from 0.055 to 0.0036). Notably, both LSE and LST biases exhibit a statistically significant exponential growth relationship with the Terrain Ruggedness Index (TRI) (R2 ≈0.75), identifying TRI, rather than absolute elevation, as the dominant control on thermal anisotropy. This study provides a comprehensive basin-scale, multi-resolution quantification of how emissivity anisotropy distorts LST estimates. These findings highlight that high-fidelity topographic correction is strongly recommended for minimizing systematic errors in hydro-climatic modelling, offering a quantitative framework for improving the physical consistency of next-generation thermal products over complex terrain.