Multi-modal AI reveals thermal environments: LST evolution and driving factors in the Yangtze River delta urban agglomeration, China
Guoyin Liu
The rapid pace of urbanization has intensified the urban heat environment, posing significant challenges to sustainable urban development. This study takes the Yangtze River Delta (YRD) urban agglomeration as its research area and utilizes MODIS summer land surface temperature (LST) remote sensing data with a spatial resolution of 1 km from 2000 to 2022. It proposes a multi-modal AI-driven integrated framework that combines Getis-Ord G spatial clustering analysis, Isolation Forest anomaly detect