Driving Factors of Land Surface Temperature in Urban Agglomerations: A Case Study in the Pearl River Delta, China

Land surface temperature (LST) in urban agglomerations plays an important role for policymakers planning. The Pearl River Delta (PRD) is one of the regions with highest densities world. This study aims to explore spatial patterns and dominant drivers LST PRD. MODIS (MYD11A2) data from 2005 2015 were used this study. First, analysis methods applied order determine identity hotspot areas (HSAs). Second, ratio index (HRI), as a metric thermal heterogeneity, was developed identify features environment across nine cities Finally, geo-detector (GD) employed LST, which included elevation, land use/land cover (LUCC), normalized difference vegetation (NDVI), impervious distribution density (ISDD), gross domestic product (GDP), population (POP), nighttime light (NLI). GD has advantages detecting without assuming linear relationships measuring combined effects drivers. results Moran’s Index showed that daytime close cluster pattern. Therefore, process led identification HSAs. HSAs concentrated central PRD distributed around estuary. HRI indicated highly heterogeneous among both nighttime. values recorded Dongguan Shenzhen during daytime. Zhaoqing, Jiangmen, Huizhou relatively lower varied city city. influence socio-economic factors on higher urbanized than low urbanization rates. For Huizhou, elevation driver period, other PRD, main changed NLI 2015. expected provide useful guidance planning agglomerations.