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<p>Rising land surface temperature and the urban heat island effect have become a serious concern for achieving worldwide urban sustainability. This work aims to investigate the connection between seasonal variability in urban land surface temperature (ULST) and the influencing factors&#xa0;in Siliguri metropolitan city. The study examines the seasonal spatial distribution of ULST by incorporating 24 factors across six variable categories, employing techniques like ordinary least-squares regression, stepwise regression, all-subsets regression, and hierarchical partitioning techniques. The results reveal that high ULST is concentrated in the city’s central areas, characterised by high built-up density, whereas low ULST is observed in the outer regions, which are defined mainly by green spaces and water bodies. In both the single-category and integrated regression models, surface properties provide the highest interpretation rate of ULST variation across all seasons. The explanatory integration rates of all influencing factors are 85.6%, 90.3%, and 85.2% in the summer, transition, and winter seasons, respectively. During the season with high (summer) and low temperatures (winter), more influencing factors are required to explain ULST than during the moderate temperature season (transition). Along with the influence of surface properties, parameters from different dimensions, such as composition and configuration of landscape, air pollutants, topography, and socioeconomic aspects, also explain the seasonal variability in ULST. This research can support the development of management strategies for urban planning based on ULST, fostering healthy living conditions and sustainable urban development.</p>

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Seasonal contrast of potential drivers of land surface temperature in urban areas of Siliguri, India

  • 期刊论文

  • 发表日期：

    2025年5月18日

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  • Sanjoy Barman,
  • Bipul Chandra Sarkar,
  • Ranjan Roy

摘要

Rising land surface temperature and the urban heat island effect have become a serious concern for achieving worldwide urban sustainability. This work aims to investigate the connection between seasonal variability in urban land surface temperature (ULST) and the influencing factors in Siliguri metropolitan city. The study examines the seasonal spatial distribution of ULST by incorporating 24 factors across six variable categories, employing techniques like ordinary least-squares regression, stepwise regression, all-subsets regression, and hierarchical partitioning techniques. The results reveal that high ULST is concentrated in the city’s central areas, characterised by high built-up density, whereas low ULST is observed in the outer regions, which are defined mainly by green spaces and water bodies. In both the single-category and integrated regression models, surface properties provide the highest interpretation rate of ULST variation across all seasons. The explanatory integration rates of all influencing factors are 85.6%, 90.3%, and 85.2% in the summer, transition, and winter seasons, respectively. During the season with high (summer) and low temperatures (winter), more influencing factors are required to explain ULST than during the moderate temperature season (transition). Along with the influence of surface properties, parameters from different dimensions, such as composition and configuration of landscape, air pollutants, topography, and socioeconomic aspects, also explain the seasonal variability in ULST. This research can support the development of management strategies for urban planning based on ULST, fostering healthy living conditions and sustainable urban development.