How 2D and 3D built environments impact urban surface temperature under extreme heat: A study in Chengdu, China

Luo, Pinyang; Yu, Bingjie; Li, Pengfei; Liang, Pengpeng; Liang, Yuan; Yang, Linchuan

doi:10.1016/j.buildenv.2023.110035

Cited by 35 publications

(8 citation statements)

References 67 publications

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“…In addition, the Qingshan District owned the highest PM 2.5 and the lowest FAR due to the large number of low-rise industrial buildings. From another perspective, a higher FAR can lead to a deeper urban canyon and accelerate the airflow velocity (Luo et al, 2023). Similarly, Jung and Yoon (2021), based on microscale simulation, also showed that FAR had a negative correlation with PM 2.5 concentrations during the period of extreme cold and high PM 2.5 pollution.…”

Section: Discussionmentioning

confidence: 99%

Exploring the relationships between 3D urban landscape patterns and PM_2.5 pollution using the multiscale geographic weighted regression model

Duan,

Cao,

Wang

et al. 2024

Progress in Physical Geography: Earth and Environment

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Fine particulate matter (PM2.5) is a major source of air pollution and exerts serious impacts on human health. The 3D urban landscape patterns can significantly affect the diffusion and emissions of PM2.5. However, studies on the relationships between 3D urban landscape patterns and PM2.5 pollution across different seasons remain understudied. With the ground-level air pollutants estimated by the remote sensing and fine-scale building information, this study applied the multiscale geographically weighted regression model to explore such relationships. Wuhan, the largest metropolis in Central China, was selected as the study area for the application of our methodology. The results showed that the direction, degree, and scale of the effect of 3D urban landscape patterns on PM2.5 pollution varied across seasons. For building height, the standard deviation of building height had a significant positive correlation with PM2.5 all year round. For building density, the building count density showed a significant positive correlation with PM2.5 in general, with the bandwidth in winter and autumn smaller than in spring and summer. The building plan area fraction exerted both positive and negative influences on PM2.5, dependent on season and location. The bandwidth of it gradually increased from spring to winter, with the effect changing from local to regional scale. For building volume, the floor area ratio showed a significant negative correlation with PM2.5 in winter and autumn, and a localized effect was found, especially in winter. The findings of this study provide practical implications for urban planning and policy making to mitigate PM2.5 pollution in the rapidly urbanizing regions.

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Section: Discussionmentioning

confidence: 99%

Exploring the relationships between 3D urban landscape patterns and PM_2.5 pollution using the multiscale geographic weighted regression model

Duan,

Cao,

Wang

et al. 2024

Progress in Physical Geography: Earth and Environment

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“…For each sampling point, the sky ratio, the building ratio and the green ratio were calculated based on the average proportion of the corresponding category of pixels in four images of different orientations. The calculation formula for the street view index system is as follows ( Luo et al, 2023 ):…”

Section: Methodsmentioning

confidence: 99%

Exploring the non-linear relationship and synergistic effect between urban built environment and public sentiment integrating macro- and micro-level perspective: a case study in San Francisco

He,

Yu,

et al. 2024

Front. Psychol.

Self Cite

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Public sentiment can effectively evaluate the public’s feelings of well-being in the urban environment and reflect the quality of the spatial environment to a certain extent. Previous studies on the relationship between public sentiment and urban built environmental factors have yielded meaningful results. However, few studies have focused on the effect of micro-built environment on public sentiment at the street level, which directly shapes people’s perceptions. In addition, the nonlinear relationship and synergistic effect among urban built environmental factors have been commonly disregarded in previous studies, resulting in an incomplete understanding of the impact of urban built environment on public emotions. Therefore, this paper takes San Francisco as a study case to explore the complex relationship between urban built environmental factors and public emotions. Specifically, this paper measures the polarity of public emotions through sentiment analysis on Twitter data, establishes a comprehensive built environment index system from both macro- and micro- perspectives, and subsequently explores the complex relationship between the urban built environment and public sentiment through the OLS model and Shapley Additive Explanation algorithm. Results show that: (1) micro-built environmental factors have a significant influence on public emotion, although they have been frequently ignored. (2) Public sentiment tends to be more positive in areas with recreation facilities, mixed land use, rich street view visual environment, suitable thermal and acoustic environment, balanced income, and a suitable degree of high population density. (3) A nonlinear relationship and threshold effect exist between the built environmental variables and the semantic orientations of public emotion. Environment improvement strategies based on the synergic effect between variables can effectively promote the generation of positive emotions. Our empirical findings can offer valuable insights to promote feelings of well-being and foster an urban development approach through strategic interventions within the urban built environment.

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“…Moreover, buildings with simple shapes can more rapidly transfer heat carried in the air through urban areas, thereby slowing down the increase in LST. Deeper canyon spaces correspond to lower daytime LST [42]. Furthermore, high-rise areas provide more public spaces and ventilation corridors.…”

Section: Impact Of 2d/3d Urban Morphology On Lstmentioning

confidence: 99%

How Does the 2D/3D Urban Morphology Affect the Urban Heat Island across Urban Functional Zones? A Case Study of Beijing, China

Du,

Wu,

Guo

et al. 2024

IJGI

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Studying driving factors of the urban heat island phenomenon is vital for enhancing urban ecological environments. Urban functional zones (UFZs), key for planning and management, have a substantial impact on the urban thermal environment through their two-dimensional (2D)/three-dimensional (3D) morphology. Despite prior research on land use and landscape patterns, understanding the effects of 2D/3D urban morphology in different UFZs is lacking. This study employs Landsat-8 remote sensing data to retrieve the land surface temperature (LST). A method combining supervised and unsupervised classification is proposed for UFZ mapping, utilizing multi-source geospatial data. Subsequently, parameters defining the 2D/3D urban morphology of UFZs are established. Finally, the Pearson correlation analysis and GeoDetector are used to analyze the driving factors. The results indicate the following: (1) In the Fifth Ring Road area of Beijing, the residential zones exhibit the highest LST, followed by the industrial zones. (2) In 2D urban morphology, the percentage of built-up landscape (built-PLAND) and Shannon’s diversity index (SHDI) are the main factors influencing LST. In 3D urban morphology, building density, the sky view factor (SVF), and the area-weighted mean shape index (shape index) are the main factors influencing LST. Therefore, low-density buildings with simple and dispersed shapes contribute to mitigating LST, while fragmented distributions of trees, grasslands, and water bodies also play important roles in alleviating LST. (3) In the interactive detection results, all UFZs show the highest interaction detection results with the built-PLAND. (4) Spatial variations are observed in the impact of different UFZs on LST. For instance, in the residential zones, industrial zones, green space zones, and public service zones, the SVF is negatively correlated with LST, while in the commercial zones, the SVF exhibits a positive correlation with LST.

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How 2D and 3D built environments impact urban surface temperature under extreme heat: A study in Chengdu, China

Cited by 35 publications

References 67 publications

Exploring the relationships between 3D urban landscape patterns and PM_2.5 pollution using the multiscale geographic weighted regression model

Exploring the relationships between 3D urban landscape patterns and PM_2.5 pollution using the multiscale geographic weighted regression model

Exploring the non-linear relationship and synergistic effect between urban built environment and public sentiment integrating macro- and micro-level perspective: a case study in San Francisco

How Does the 2D/3D Urban Morphology Affect the Urban Heat Island across Urban Functional Zones? A Case Study of Beijing, China

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How 2D and 3D built environments impact urban surface temperature under extreme heat: A study in Chengdu, China

Cited by 35 publications

References 67 publications

Exploring the relationships between 3D urban landscape patterns and PM2.5 pollution using the multiscale geographic weighted regression model

Exploring the relationships between 3D urban landscape patterns and PM2.5 pollution using the multiscale geographic weighted regression model

Exploring the non-linear relationship and synergistic effect between urban built environment and public sentiment integrating macro- and micro-level perspective: a case study in San Francisco

How Does the 2D/3D Urban Morphology Affect the Urban Heat Island across Urban Functional Zones? A Case Study of Beijing, China

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Exploring the relationships between 3D urban landscape patterns and PM_2.5 pollution using the multiscale geographic weighted regression model

Exploring the relationships between 3D urban landscape patterns and PM_2.5 pollution using the multiscale geographic weighted regression model