Multidimensional assessment of the spatiotemporal evolution, driving mechanisms, and future predictions of urban heat islands in Jinan, China

. (3) Synergistic interactions, especially between topographic factors (such as the Digital Elevation Model, DEM) and land-use indices (e.g., normalized difference built-up index, NDBI; normalized difference vegetation index, NDVI), were found to significantly influence LST variations. (4) The Oscillating Sequence Grey Model (OSGM), optimized for handling oscillating data sequences, demonstrated superior predictive accuracy, projecting a 20.72% increase in extreme high-temperature zones and a 40.61% reduction in moderate-high-temperature zones by 2047. These findings offer actionable strategies for urban planning and climate adaptation, aiming to mitigate thermal risks and inform future policies for urban sustainability and resilience. This research underscores the importance of integrating spatial and predictive analyses to inform urban planning and climate adaptation strategies, contributing to the mitigation of thermal risks and the development of sustainable urban policies.