Seasonal Dependence of Topographic Effect on Mountainous Land Surface Temperature Retrieval: Insights From Landsat-8 Data

Land surface temperature (LST) is a key parameter for characterizing land–atmosphere interactions, energy balance, and ecological processes. Previous studies have incorporated topographic effects in mountainous LST (MLST) retrieval, yet systematic quantification of the seasonal magnitude of these effects remains lacking. In this study, Landsat-8 thermal infrared data are employed from the sensor's observational perspective, and representative images for spring, summer, autumn, and winter are selected across the Tibet Plateau, enabling the determination of seasonal topographic effects (ΔLST), where ΔLST refers to the difference between LST retrieved without and with consideration of topographic effects. Results indicate that ΔLST is primarily controlled by topographic factors, including small-scale self-heating parameters (SSP), sky view factor (SVF), and land surface emissivity (LSE). Among the seasons, topographic effect is most pronounced in summer, with ΔLST exceeding 8 K in rugged areas with low emissivity. ΔLST exhibits clear dependence on slope and aspect, with south-facing slopes generally higher than north-facing slopes, and increasing with slope steepness, indicating that steep slopes are more sensitive to solar radiation. Further analysis reveals that ΔLST is positively correlated with SSP, and negatively correlated with SVF and LSE, with the strongest correlations observed in summer, suggesting that topographic radiation imbalance is the dominant mechanism controlling MLST variability. Note that when SSP is close to 1.0, SVF is close to 0.0, and LSE is close to 1.0, ΔLST is minimal, and topographic effects on LST can be neglected. Overall, the seasonal pattern of ΔLST follows the order: summer > autumn ≈ spring > winter, and a recent increasing trend in ΔLST implies enhanced thermal responses in mountainous regions under climate warming. These findings improve understanding of topographic influences on MLST retrieval and provide more reliable LST data for studies of energy balance, evapotranspiration, and ecological processes.