Identification of Key Drivers of Land Surface Temperature Within the Local Climate Zone Framework

The surface urban heat island (SUHI) effect, driven by human activities and land cover changes, leads to elevated temperatures in urban areas, posing challenges to sustainability, public health, and environmental quality. While SUHI drivers at large scales are well-studied, finer-scale thermal variations remain underexplored. This study employed the Local Climate Zones (LCZs) framework to analyze land surface temperature (LST) dynamics in Zhengzhou, China. Using 2022 mean LST data derived from a single-channel algorithm, combined with field surveys and remote sensing techniques, we examined 30 potential driving factors spanning natural and anthropogenic conditions. Results show that built-type LCZs had higher average LSTs (31.10 &deg:C) compared with non-built LCZs (28.91 &deg:C), with non-built LCZs showing greater variability (10.48 &deg:C vs. 6.76 &deg:C). Among five major driving factor categories, landscape pattern indices dominated built-type LCZs, accounting for 44.5% of LST variation, while Tasseled Cap Transformation indices, particularly brightness, drove 42.8% of the variation in non-built-type LCZs. Partial dependence analysis revealed that wetness and landscape fragmentation reduce LST in built-type LCZs, whereas GDP, imperviousness, and landscape cohesion increase it. In non-built LCZs, population density, connectivity, and brightness raise LST, while wetness and atmospheric dryness provide cooling effects. These findings highlight the need for LCZ-specific SUHI mitigation strategies. Built-type LCZs require urban form optimization, enhanced landscape connectivity, and expanded green infrastructure to reduce heat accumulation. Non-built LCZs benefit from maintaining soil moisture, addressing atmospheric dryness, and optimizing vegetation configurations. This study provides actionable insights for sustainable thermal environment management and urban resilience.