Quantitative Analysis and Spatial Pattern Research of Built-Up Environments and Surface Urban Heat Island Effect in Beijing’s Main Urban Area

Abstract

The surface urban heat island (SUHI) phenomenon, predominantly influenced by factors associated with the built-up environment, is prominent in large metropolitan areas. To effectively mitigate the escalating thermal environment challenges arising during large cities’ developmental planning, rigorously examining the spatial interdependencies between the built-up environment and the SUHI phenomenon is imperative. Employing Beijing's primary urban area as a case study, this research addresses the gap in the systematic analysis of spatial correlations between the built-up environment and SUHI within the urban heat island effect research domain. The study leverages Landsat-8 satellite data spanning 2016–2020, Sentinel-2 land-use classification data, and 2020 digital elevation model (DEM) data, integrating them with geospatial data processing techniques to probe the multifaceted associations between the built-up environment and SUHI in a 1 × 1-km grid-based local-scale model. This investigation is distinguished by developing a Comprehensive Built-up Environment System Index, synthesized through multisource data and multidimensional methodologies. The study culminates in the following key findings: (1) Between 2016 and 2020, Beijing's primary urban area manifested an ascending spiral trend in the SUHI effect, with the heat island morphology exhibiting nonuniformity across the four seasons. (2) In the historical summer heat island scenarios of Beijing's primary urban area, the architectural and roadway environments demonstrated a consistently positive correlation with the SUHI effect. (3) Excluding the average number of floors parameter, all remaining urban built-up environment parameters exhibited a significant association with SUHI fluctuations. This research provides valuable insights on the following aspects for urban planners, policymakers, and practitioners addressing the surface urban heat island effect in Beijing's main urban area. (1) Urban heat island mitigation: Influential urban parameters, like building density, road connectivity coefficient, and green space, significantly impact surface urban heat island (SUHI) intensity. Targeted strategies, such as increasing green spaces and implementing cool roofs, can mitigate the SUHI effect and improve urban thermal comfort. (2) Season-specific planning: Recognizing seasonal variations in SUHI intensity allows for season-specific urban planning. Implementing cooling strategies, like urban cooling parks and remarkable pavement technologies, during summer in heat-prone areas efficiently helps manage thermal environments. (3) Data-driven decision-making: Leveraging geospatial data and advanced analytics fosters data-driven urban planning. Policymakers can use the Comprehensive Built-up Environment System Index to assess the impact of urban parameters on SUHI intensity, facilitating evidence-based policy formulation and adaptive management. (4) Climate-resilient urban design: Integrating SUHI mitigation measures, such as green infrastructure, cool roofs, and reflective materials, helps enhance climate resilience. Urban designers can create sustainable and climate-resilient urban environments, promoting long-term urban sustainability and well-being.