Day–Night Synergy Between Built Environment and Thermal Comfort and Its Impact on Pedestrian Street Vitality: Beijing–Chengdu Comparison
Abstract
1. Introduction
1.1. Climate Environment and Its Impact on Urban Vitality
1.2. The Relationship Between the Built Environment and Urban Vitality
- How do individual built environment factors influence the vitality of pedestrian commercial streets and what trends do they exhibit?
- How do the interactions among different built environment factors affect street vitality?
2. Data and Methods
2.1. Research Framework
2.2. Study Area
2.3. Data Processing and Verification
2.3.1. Independent Variables
- Shop width (SW)
- 2.
- Street width
- 3.
- Green view ratio (GVR)
- 4.
- Sky visibility
- 5.
- Number of items of street furniture
- 6.
- Physiological equivalent temperature (PET)
- 7.
- Store interface transparency (FT)
- 8.
- Billboard density
2.3.2. Dependent Variable
2.4. Interpretable Machine Learning Approach
3. Results
3.1. Spatiotemporal Dynamics of Pedestrian Commercial Street Vitality
3.2. Vitality Impact Magnitude of Individual Built Environment Factors
3.3. Synergistic Effects of Built Environment Factors on Street Vitality
4. Discussion
4.1. Diurnal and Nocturnal Effects of Built Environment Factors on Street Vitality
4.2. Differences in the Impact of Built Environment Factors on Street Vitality Across Different Cities
4.3. Limitations and Perspectives
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Spatial Element Indicators | Calculation Method | Sources |
---|---|---|
Shop width (SW) | () storefront width of shop i, () total street-facing frontage of all shops on one side of shop i, () street-facing width of the commercial street for shop i. | Data for storefront lengths and commercial interface length from field measurement of the commercial pedestrian streets under study, or from architectural plans/drawings of the street and shop units. |
Street width | () Street width of pedestrian commercial street area i, () total area of pedestrian commercial street area i, () street length of pedestrian commercial street area i. | Total street area come from urban planning GIS data, or be calculated via field-measured length and width (if regular shape), length of the line connecting midpoints of entrances/exits from field measurement or spatial mapping tools. |
Green view ratio (GVR) | (GVR) green view ratio, () area of greenery in the pedestrian’s field of view, () total visual area in the pedestrian’s field of view. | Street view image segmentation algorithms, street view images from on-site photography (using cameras to capture pedestrian-level views of the street) or from existing street view datasets (e.g., Google Street View). |
Sky visibility | (GVR) sky visibility, () area of the sky in the pedestrian’s field of view, () total visual area in the pedestrian’s field of view. | Relying on street view image segmentation algorithms. Street view images from on-site capture or existing street view data sources. |
Number of items of street furniture | (N) number of items of street furniture in the pedestrian’s field of view, () the piece of street furniture, (M) total number of street furniture in the pedestrian’s field of view. | Street view image recognition algorithms (involve object detection models like YOLO, trained to identify street furniture types), street view images from on-site photography or existing datasets. |
Physiological equivalent temperature (PET) | (PET) physiological equivalent temperature, an indicator of thermal comfort, (T) air temperature (°C), (RH) relative humidity (%), (WS) wind speed (m/s), (M) human metabolic rate (typically standardized to a sedentary state, ~80 W/m2), (R) radiant heat exchange (including solar and long-wave radiation, W/m2), (C) clothing thermal resistance (typically set at 0.5 clo for summer). | Air temperature, humidity, wind speed data from meteorological stations (either local fixed stations near the study area or mobile weather sensors deployed in the field). ENVI-met software (with input data from the aforementioned meteorological factors and possibly 3D models of the street environment built from architectural and urban data). |
Store interface transparency (FT) | (FT) sore interface transparency, () area of transparent shop interfaces in the pedestrian’s field of view, () total visual area in the pedestrian’s field of view. | Street view image segmentation algorithms. Street view images from on-site capture (pedestrian-level photos of storefronts) or existing street view resources. |
Billboard density | (BD) billboard density, () area of billboards in the pedestrian’s field of view, () total visual area in the pedestrian’s field of view. | Street view image segmentation algorithms, street view images from on-site photography or existing street view datasets. |
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Zhang, J.; Li, X.; Lian, H.; Li, H.; Zhang, J. Day–Night Synergy Between Built Environment and Thermal Comfort and Its Impact on Pedestrian Street Vitality: Beijing–Chengdu Comparison. Buildings 2025, 15, 2118. https://doi.org/10.3390/buildings15122118
Zhang J, Li X, Lian H, Li H, Zhang J. Day–Night Synergy Between Built Environment and Thermal Comfort and Its Impact on Pedestrian Street Vitality: Beijing–Chengdu Comparison. Buildings. 2025; 15(12):2118. https://doi.org/10.3390/buildings15122118
Chicago/Turabian StyleZhang, Jinjiang, Xuan Li, Haitao Lian, Haozhe Li, and Junhan Zhang. 2025. "Day–Night Synergy Between Built Environment and Thermal Comfort and Its Impact on Pedestrian Street Vitality: Beijing–Chengdu Comparison" Buildings 15, no. 12: 2118. https://doi.org/10.3390/buildings15122118
APA StyleZhang, J., Li, X., Lian, H., Li, H., & Zhang, J. (2025). Day–Night Synergy Between Built Environment and Thermal Comfort and Its Impact on Pedestrian Street Vitality: Beijing–Chengdu Comparison. Buildings, 15(12), 2118. https://doi.org/10.3390/buildings15122118