Temporal trend of the frequency and maximum durations of surface urban heat islands over global cities

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106141 - 106141

Опубликована: Янв. 1, 2025

Язык: Английский

The Spatiotemporal Evolution and Driving Forces of the Urban Heat Island in Shijiazhuang

Remote Sensing, Год журнала: 2025, Номер 17(5), С. 781 - 781

Опубликована: Фев. 23, 2025

As a comprehensive reflection of the thermal characteristics urban environment, heat island (UHI) effect has triggered series ecological and environmental issues. Existing studies on UHI in Shijiazhuang, capital Hebei Province, China, have primarily focused spatial–temporal distribution migration trends, with less focus influences other contributing factors. This study focuses Shijiazhuang city, using Landsat ETM+/OLI data from 2000 to 2020 analyze spatiotemporal traits effect. The mono-window algorithm (MW) was used retrieve land surface temperatures (LSTs), seasonal autoregressive integrated moving average (SARIMA) model predict LST trends. Key factors such as normalized difference vegetation index (NDVI), digital elevation (DEM), population (POP), precipitation (PPT), impervious (IPS), potential evapotranspiration (PET), particulate matter 2.5 (PM2.5), night light (NL) were analyzed spatial autocorrelation explore their dynamic relationship UHI. Specifically, multi-scale analysis developed search for optimum scale, enabling assessment evolution drivers Shijiazhuang. showed pronounced clustering, expanding annually by 44.288 km2, southeastward shift. Autumn exhibited greatest reduction UHI, while predictions suggested peak summer 2027. According bivariate clustering analysis, NDVI most influential factor mitigating IPS spatially significant enhancement central areas. Other generally promoted after 2005. geographically weighted regression (MGWR) best fitted at 3 km × scale. Considering joint effects multiple factors, ranking prediction is follows: PET > DEM PPT PM2.5 NL POP. interactive effects, especially between DEM, reach value 0.72. These findings may address concerns regarding both future trends mitigation indications variations

Язык: Английский

A Comprehensive Validation Scheme for Satellite-derived Land Surface Temperature Dataset

IEEE Transactions on Geoscience and Remote Sensing, Год журнала: 2024, Номер 62, С. 1 - 12

Опубликована: Янв. 1, 2024

Язык: Английский