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

ABSTRACT: Understanding the spatiotemporal distribution of land surface temperature (LST) is crucial for managing urban thermal environments and mitigating urban heat island (UHI) effects. This study addresses the challenge of quantifying the complex interactions among natural and anthropogenic factors driving LST variations, while leveraging advanced modeling techniques to predict future thermal risks in rapidly urbanizing regions. By analyzing the evolution of LST in Jinan city, China, from 2002 to 2022, and forecasts future trends using advanced spatial analysis and predictive modeling techniques. Directional shifts in LST were quantified using the quadrant azimuth method and the standard deviation ellipse method, both of which analyze spatial distribution and dispersion. To identify the key driv

SUBMITTER: Tan L 

PROVIDER: S-EPMC11961603 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature