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Advanced Study on Urban Environment by Big Data Analytics
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Advanced Study on Urban Environment by Big Data Analytics

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Energy, Physics, Environment, and Systems".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 6430

Special Issue Editors

Dr. Lei Wang

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Guest Editor
Institute of Remote Sensing and Geographical Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Interests: street view; urban perception; GeoAI; urban big data; urban visual intelligence
Prof. Dr. Jie He

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Guest Editor
School of Architecture, Harbin Institute of Technology, Shenzhen 518055, China
Interests: digital humanities; digital archaeology and digital heritage; landscape archaeology; RS archaeology
Special Issues, Collections and Topics in MDPI journals
Dr. Mingshuai Li

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Guest Editor
College of Civil Engineering and Architecture, Hebei University, Baoding 071000, China
Interests: heritage conservation; remote sensing; The Great Wall; heritage site disease; human settlements
Dr. Fei Yang

E-Mail Website
Guest Editor
College of Landscape Architecture, Northeast Forestry University, Harbin 150040, China
Interests: urban blue-green space; cooling capacity; urban thermal environment; digital modeling; urban planning and design
Dr. Xinyuan Dang

E-Mail Website
Guest Editor
Department of Civil Engineering, Building Physics and Sustainable Design Section, KU Leuven, 3001 Leuven, Belgium
Interests: heat, air and moisture (HAM) modeling; building performance; heritage conservation theories and technologies; heritage governance criticism; sustainable and healthy built environment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Street-level imagery and geospatial artificial intelligence (GeoAI) are revolutionizing urban studies by offering new ways to assess cityscapes and human perceptions of the built environment. This Special Issue of Buildings focuses on leveraging technologies such as street-view imagery, digital modeling and digital heritage to enhance urban perception research and heritage conservation, contributing to sustainable and healthy built environments.

We welcome interdisciplinary contributions spanning any city or cultural context, without restriction to specific methods or study types. Potential research directions include GeoAI-driven analysis of street-view images for urban built-environment evaluation, digital documentation and modeling of heritage sites for conservation and innovative frameworks linking urban perception data with planning for sustainability. By gathering diverse insights, this Special Issue aims to advance the understanding of how digital tools can preserve cultural heritage and inform healthier, more sustainable urban built environments.

Dr. Lei Wang
Prof. Dr. Jie He
Dr. Mingshuai Li
Dr. Fei Yang
Dr. Xinyuan Dang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • urban visual intelligence
  • urban perception
  • urban built environment
  • urban thermal environment
  • heritage conservation
  • digital heritage
  • urban planning and design
  • urban mobility

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Published Papers (9 papers)

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Research

30 pages, 4202 KB  
Article
Study on Post-Use Evaluation and Optimization Strategies for the Cultural Tourism Landscape of Xidajie Street in Baoding from the Perspective of Immersive Experience
by Ke Ni, Ji Feng, Chenyu Wang, Yanwei Zhou and Heng Wang
Buildings 2026, 16(6), 1259; https://doi.org/10.3390/buildings16061259 - 23 Mar 2026
Viewed by 789
Abstract
In the context of immersive technologies deeply integrated into the cultural tourism industry, immersive cultural tourism has become an important means of heritage revitalization. Immersive experience is both a crucial consumer element and a key indicator for evaluating the attractiveness of cultural tourism [...] Read more.
In the context of immersive technologies deeply integrated into the cultural tourism industry, immersive cultural tourism has become an important means of heritage revitalization. Immersive experience is both a crucial consumer element and a key indicator for evaluating the attractiveness of cultural tourism landscapes. This study evaluates the post-use experience of the cultural tourism landscape of Xidajie Street in Baoding from the perspective of tourist immersion. Through a literature review, investigation of typical immersive districts, and expert interviews, we extract immersive cultural tourism landscape evaluation criteria based on a depth model of immersion, focusing on three dimensions: narrative, enclosure, and interaction. Subjective perception data from tourists is then collected through a survey, and IPA (Importance–Performance Analysis) is employed to identify the strengths and weaknesses of Xidajie’s cultural tourism landscape. The results show that Xidajie excels in spatial environment shaping and historical preservation, but has room for improvement in cultural narrative extension, contextual immersion, and interactive experiences. Therefore, strategies are proposed to enhance the cultural IP, establish a complete narrative structure, create authentic enveloping environments, and enrich interactive games to build a high-quality online and offline immersive cultural tourism landscape. This aims to promote the renewal of Xidajie and the dynamic transmission of Baoding’s local culture. Full article
(This article belongs to the Special Issue Advanced Study on Urban Environment by Big Data Analytics)
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23 pages, 10459 KB  
Article
How Do Street Physical Environments Shape Pedestrian Safety Perception? Evidence from Street-View Imagery, Machine Learning, and Multiscale Geographically Weighted Regression
by Zhongshan Huang, Kuan Lu, Wenming Cai and Xin Han
Buildings 2026, 16(5), 920; https://doi.org/10.3390/buildings16050920 - 26 Feb 2026
Viewed by 558
Abstract
In high-density urban cores, pedestrian safety perception is shaped not only by street physical environments but also by pronounced spatial heterogeneity. However, existing studies often rely on global regression or small-sample surveys, making it difficult to simultaneously reveal city-scale regularities and localized mechanisms. [...] Read more.
In high-density urban cores, pedestrian safety perception is shaped not only by street physical environments but also by pronounced spatial heterogeneity. However, existing studies often rely on global regression or small-sample surveys, making it difficult to simultaneously reveal city-scale regularities and localized mechanisms. Taking Futian District, Shenzhen, as a case study, this study develops an integrated analytical framework that combines street-view imagery, machine learning, and multiscale geographically weighted regression (MGWR) to measure pedestrian safety perception at the city scale and to unpack its spatial mechanisms. The results show that model explanatory power improves markedly after accounting for spatial non-stationarity, indicating strong context dependence in the formation of pedestrian safety perception. MGWR further reveals clear multiscale differentiation across streetscape visual elements: greenery-related elements (e.g., tree and plant) exhibit near-global and consistently positive effects, whereas traffic exposure and interface-related elements (e.g., car, road, and wall) operate more locally, with both the direction and magnitude of their effects varying substantially with neighborhood structure and traffic contexts. These findings suggest that the impacts of individual street elements on pedestrian safety perception are not universally transferable and should be interpreted within a spatial-scale and contextual framework. By integrating machine learning-based prediction with MGWR-based spatial interpretation, this study enables both efficient city-scale measurement and multiscale mechanism identification of pedestrian safety perception, providing empirical support for safety perception-oriented street planning and fine-grained urban design. Full article
(This article belongs to the Special Issue Advanced Study on Urban Environment by Big Data Analytics)
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30 pages, 146632 KB  
Article
Form Meets Flow: Linking Historic Corridor Morphology to Multi-Scale Accessibility and Pedestrian Interface on Beishan Street, West Lake
by Dongxuan Li, Jin Yan, Shengbei Zhou, Yingning Shen, Hongjun Peng, Zhuoyuan Du, Xinyue Gao, Yankui Yuan, Ming Du and Jun Wu
Buildings 2026, 16(5), 889; https://doi.org/10.3390/buildings16050889 - 24 Feb 2026
Viewed by 497
Abstract
Historic linear corridors in living-heritage settings concentrate identity, everyday mobility, and visitor experience. Balancing authenticity, adaptability, and publicness therefore benefits from evidence that jointly characterizes long-term physical change, network accessibility, and eye-level interface conditions. Existing assessments often focus on façades or single time [...] Read more.
Historic linear corridors in living-heritage settings concentrate identity, everyday mobility, and visitor experience. Balancing authenticity, adaptability, and publicness therefore benefits from evidence that jointly characterizes long-term physical change, network accessibility, and eye-level interface conditions. Existing assessments often focus on façades or single time slices, leaving limited evidence that relates decades of built-fabric reconfiguration (changes in building footprints, street edges, and open-space fragmentation) to multi-scale accessibility and pedestrian-facing qualities. We propose an integrated and interpretable workflow for the Beishan Street corridor in the West Lake World Heritage core (Hangzhou) over 1929–2024. Scale-sensitive morphological metrics, multi-radius network measures (integration and centrality), and street-view semantic segmentation are aligned at corridor-segment resolution and examined together with segment-level functional intensity derived from POIs using transparent linear models. The results indicate a long-term shift from a lakeshore-led to a road-led spatial logic, followed by post-2000 stabilization near saturation. Average integration increases, while the high-integration tail becomes thinner. In connector-removal scenarios, the eastern segment shows a relative accessibility decline, and a central hinge node emerges as a vulnerability hotspot (bottleneck) where through-movement concentrates. Eye-level profiles differ by segment: the west exhibits maximal canopy and lower sky visibility, the center shows stronger continuous walls around compounds with intermittent forecourt openings, and the east is characterized by compact residential heritage frontage with low vegetation. Segment-level associations suggest that address and wayfinding density tends to co-occur with clearer frontages, wider sky cones, and stronger tree cover. Transportation-related and access/passage facilities tend to co-occur with higher ground-plane legibility, measured as wider and more continuous road and sidewalk surfaces. Medical and government clusters tend to co-occur with lower sky openness. Recommended actions include the following: (1) mesh-aware protection of key connectors and the hinge, (2) segment-specific targets for façade share and ground cues with planned punctuations, (3) tailored interface standards for institutional clusters, (4) scalable address and wayfinding systems, and (5) event staging that preserves effective roadway and sidewalk capacity. Full article
(This article belongs to the Special Issue Advanced Study on Urban Environment by Big Data Analytics)
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21 pages, 15239 KB  
Article
Spatiotemporal Distribution of Ancient Stone Bridges in Wuxi, China and Their Relationship with the Natural Environment
by Hongjun Peng, Ping Li, Zhuoyuan Du, Haoran Jin, Xinyue Gao, Shengbei Zhou and Chunyan Zhang
Buildings 2026, 16(4), 797; https://doi.org/10.3390/buildings16040797 - 15 Feb 2026
Viewed by 516
Abstract
As a significant component of hydraulic cultural heritage within the Grand Canal Cultural Belt, ancient stone bridges serve as vital physical evidence reflecting the evolutionary patterns of water conservancy and settlement spaces in Wuxi. Consequently, understanding their distribution holds critical significance for the [...] Read more.
As a significant component of hydraulic cultural heritage within the Grand Canal Cultural Belt, ancient stone bridges serve as vital physical evidence reflecting the evolutionary patterns of water conservancy and settlement spaces in Wuxi. Consequently, understanding their distribution holds critical significance for the holistic protection and revitalized utilization of the heritage. This study investigates 118 ancient stone bridges in Wuxi, China, employing ArcGIS spatial analysis methods, specifically average nearest neighbor, kernel density estimation, and standard deviational ellipse, to examine spatiotemporal characteristics. Additionally, a random forest (RF) model is utilized to quantify the importance of natural environmental factors influencing their distribution. The results reveal the following: (1) Temporally, the distribution transitioned from a random pattern in the Song Dynasty to a highly clustered pattern during the Ming, Qing, and Republic of China periods. (2) Spatially, the distribution centroid exhibited a distinct southwestward trend, evolving from a dispersed structure into a multi nuclei aggregation model centered on Yixing and Wuxi City. (3) Environmentally, bridges are predominantly located in low-elevation plains, gentle slopes (2° to 5°), and stable zones far from geological hazards. They exhibit a preference for northeast and northwest aspects, with the highest concentration within 100 m of rivers and in paddy or yellow–brown soil regions. (4) The RF model identifies rivers as the absolute dominant factor, followed by aspect, geological hazards, slope, and elevation, while soil factors have the lowest importance. These findings enrich the conservation theory for hydraulic cultural heritage and provide a scientific basis for the risk assessment, hierarchical protection, and integrated tourism planning of ancient stone bridges. Full article
(This article belongs to the Special Issue Advanced Study on Urban Environment by Big Data Analytics)
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25 pages, 33282 KB  
Article
Research on the Design Methodology of Children’s Play Spaces in Urban Communities Based on EFA–SEM
by Hui Liu, Yi Zhong, Yujia Li, Yajie Zhao, Shiyi Cao and Honglei Chen
Buildings 2026, 16(4), 780; https://doi.org/10.3390/buildings16040780 - 13 Feb 2026
Cited by 1 | Viewed by 500
Abstract
Urban community children’s play spaces play a crucial role in promoting both physical and mental health, significantly influencing children’s development and fostering a sense of belonging to the community. However, existing design practices often fail to adequately address the complex behavioral and emotional [...] Read more.
Urban community children’s play spaces play a crucial role in promoting both physical and mental health, significantly influencing children’s development and fostering a sense of belonging to the community. However, existing design practices often fail to adequately address the complex behavioral and emotional needs of children in these spaces. To overcome this gap, there is an urgent need for a system that can effectively respond to these complexities, thereby enhancing children’s play experiences and their attachment to the space. This study seeks to optimize the design of children’s play spaces in urban communities through a quantitative approach based on Exploratory Factor Analysis (EFA) and Structural Equation Modeling (SEM). First, multi-dimensional data concerning children’s physical environment, subjective perceptions, play behaviors, and satisfaction were gathered through field surveys and questionnaires. Reliability and validity assessments were conducted to ensure data quality. Subsequently, EFA was applied to perform dimensionality reduction and identify the underlying structure, resulting in the extraction of six key factors that influence children’s play experiences. Finally, SEM was utilized to construct a structural model, test hypotheses, and quantify the relationships between the identified dimensions. The results demonstrate that the EFA-SEM framework effectively transforms subjective concepts into actionable design parameters, meeting user needs and providing a solid scientific foundation for the design of children’s play spaces in urban communities. Full article
(This article belongs to the Special Issue Advanced Study on Urban Environment by Big Data Analytics)
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28 pages, 48361 KB  
Article
Influence of Urban Morphological Characteristics on Street-Level Urban Heat Risk: A Geographically Weighted Machine Learning Approach
by Yuqiao Zhang, Jun Wu, Kewei Zhong, Shengbei Zhou, Yankui Yuan, Qi Wang and Yuning Liu
Buildings 2026, 16(4), 725; https://doi.org/10.3390/buildings16040725 - 11 Feb 2026
Viewed by 628
Abstract
As extreme heat events become increasingly frequent worldwide, there is an urgent need for fine-scale assessment of urban heat risk and for identifying its key determinants. Conventional approaches often struggle to capture complex intra-urban spatial heterogeneity, limiting effective heat risk governance and resource [...] Read more.
As extreme heat events become increasingly frequent worldwide, there is an urgent need for fine-scale assessment of urban heat risk and for identifying its key determinants. Conventional approaches often struggle to capture complex intra-urban spatial heterogeneity, limiting effective heat risk governance and resource allocation. This study applies the Hazard–Exposure–Vulnerability–Adaptation (HEVA) framework by integrating remote sensing, road network, and socio-demographic data. Using the CRITIC weighting method, we quantify and map a street-level heat risk index (HRI) in Tianjin, China. We further employ geographically weighted machine learning models to identify dominant drivers and to characterise nonlinear effects, interaction patterns, and spatially varying relationships. Model reliability is assessed by benchmarking geographically weighted models against global nonlinear baselines under three-fold cross-validation; GW-XGBoost achieves comparable explanatory power to the best global model (R2 = 0.672) while yielding lower prediction errors (MAE = 0.142), supporting robust spatial inference. Results show that elevated heat risk is not confined to the urban core; instead, it is more pronounced in peripheral transitional zones around central districts. These areas often exhibit coincident heat stress and high population exposure, a higher concentration of vulnerable groups and ageing residential neighbourhoods, and comparatively limited access to medical and cooling resources. Mechanistically, greater development intensity is generally associated with higher heat risk, whereas higher vegetation cover tends to reduce risk; however, the strength and, in some locations, the direction of these effects vary substantially across streets. These findings suggest that heat risk management should prioritise peripheral transitional zones. Targeted interventions should balance development intensity, expand effective greening and shading, and improve the provision and accessibility of healthcare and cooling services to reduce street-level heat risk. Full article
(This article belongs to the Special Issue Advanced Study on Urban Environment by Big Data Analytics)
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33 pages, 8191 KB  
Article
Revitalization of Historic Buildings in China: A Strategic Framework for Adaptive Reuse and Cultural Revitalization of the Xuzhou Urban Area
by Minghao Zhang, Yuxuan Cheng, Fang Liu and Qian Liu
Buildings 2026, 16(4), 700; https://doi.org/10.3390/buildings16040700 - 8 Feb 2026
Viewed by 740
Abstract
Historic buildings are crucial for urban cultural continuity and sustainable development, but their protection and adaptive reuse are often constrained by institutional, financial, and managerial challenges. This study, using five historic buildings in Xuzhou as case studies, analyzes the key mechanisms influencing adaptive [...] Read more.
Historic buildings are crucial for urban cultural continuity and sustainable development, but their protection and adaptive reuse are often constrained by institutional, financial, and managerial challenges. This study, using five historic buildings in Xuzhou as case studies, analyzes the key mechanisms influencing adaptive reuse, focusing on the impact of property rights structures, governance systems, and operational models on protection and reuse outcomes. Through semi-structured interviews with government officials, property owners, and the public, combined with on-site surveys and historical data, the study identifies fragmented property rights, limited funding, and homogeneous reuse models as the main barriers. It further highlights that clear property responsibility, a coordinated institutional framework, and diversified operational strategies are linked to successful adaptive reuse. The paper proposes a comprehensive framework covering policy regulation, financial investment, cultural activation, and restoration techniques. Five strategic recommendations are made: policy optimization, diversified funding, strengthened awareness, operational model upgrades, and multi-dimensional revitalization strategies. This research offers an empirical framework for the adaptive reuse of historic buildings, providing insights applicable to similar institutional and developmental contexts. Full article
(This article belongs to the Special Issue Advanced Study on Urban Environment by Big Data Analytics)
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22 pages, 9314 KB  
Article
Road-Type-Specific Streetscape Renewal Effects on Urban Beauty Perception: A Spatiotemporal SHAP Analysis Using Historical Street Views
by Wenhan Li, Yinzhe Li, Lingling Zhang, Jiahui Gao, Shanshan Xie and Yan Feng
Buildings 2026, 16(3), 653; https://doi.org/10.3390/buildings16030653 - 4 Feb 2026
Viewed by 474
Abstract
Amid China’s shift from a model of urban “incremental expansion” to one focused on “stock optimization”, the renewal of streetscapes has taken center stage as a critical approach to improving the human experience within urban environments. However, empirical insight into how visual interventions [...] Read more.
Amid China’s shift from a model of urban “incremental expansion” to one focused on “stock optimization”, the renewal of streetscapes has taken center stage as a critical approach to improving the human experience within urban environments. However, empirical insight into how visual interventions affect aesthetic perception across different road types remains notably limited. This study addresses that gap through a spatiotemporal investigation of Zhengzhou’s streetscape transformations between 2017 and 2022. Major roads were categorized into four functional types—freeway, under-freeway, regular road, and tunnel—to better capture perceptual variation. Leveraging a Fully Convolutional Network (FCN), we extracted nine visual components from historical street views and paired them with crowd-sourced “beauty” ratings from the MIT Place Pulse 2.0 dataset. Statistical analyses, including paired t-tests and Kernel Density Estimation (KDE), indicated marked improvements in perceived beauty following renewal, with the exception of tunnel segments. Through Random Forest (RF) regression and SHapley Additive exPlanations (SHAP) interpretation, greening emerged as the most influential driver of aesthetic enhancement—most prominently on regular roads (SHAP = 2.246). The impact of renewal was found to be context-specific: green belts were most effective in under-freeway areas (SHAP = +0.8), while improvements to pavement (SHAP = +0.97) and street vitality were key for regular roads. Notably, SHAP analysis revealed non-linear relationships, such as diminishing perceptual returns when green coverage exceeded certain thresholds. These findings inform a “visual renewal–perceptual response” framework, offering data-driven guidance for adaptive, human-centered upgrades in high-density urban settings. Full article
(This article belongs to the Special Issue Advanced Study on Urban Environment by Big Data Analytics)
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22 pages, 6823 KB  
Article
Exploring the Spatial Distribution of Traditional Villages in Yunnan, China: A Geographic-Grid MGWR Approach
by Xiaoyan Yin, Shujun Hou, Xin Han and Baoyue Kuang
Buildings 2026, 16(2), 295; https://doi.org/10.3390/buildings16020295 - 10 Jan 2026
Cited by 1 | Viewed by 1040
Abstract
Traditional villages are vital carriers of cultural heritage and key foundations for rural revitalization and sustainable development, yet rapid urbanization increasingly threatens their survival, making it necessary to clarify their spatial distribution and driving mechanisms to support effective conservation and rational utilization. Yunnan [...] Read more.
Traditional villages are vital carriers of cultural heritage and key foundations for rural revitalization and sustainable development, yet rapid urbanization increasingly threatens their survival, making it necessary to clarify their spatial distribution and driving mechanisms to support effective conservation and rational utilization. Yunnan Province, home to 777 nationally recognized traditional villages and the highest number in China, offers a representative context for such analysis. Methodologically, this study uses a 12 km × 12 km geographic grid (3005 cells) rather than administrative units. The count of catalogued traditional villages in each cell is taken as the dependent variable, and nine indicators selected from five dimensions (traffic accessibility, natural topography, climatic conditions, socioeconomic factors, and historical and cultural factors) serve as explanatory variables. Assuming that relationships between villages and their environment are spatially nonstationary and operate at multiple spatial scales, we combine spatial autocorrelation analysis with a multiscale geographically weighted regression (MGWR) model to detect clustering patterns and estimate location-specific coefficients and bandwidths. The results indicate that: (1) traditional villages in Yunnan exhibit significant clustering, with over 60% concentrated in Dali, Baoshan, Honghe, and Lijiang; (2) the spatial pattern follows a “more in the northwest, fewer in the southeast, dense in mountainous areas” distribution, shaped by both natural and socioeconomic factors; (3) natural geographic factors show the strongest associations, with sunshine duration and water availability strongly promoting village presence, while slope exhibits regionally differentiated effects; (4) socioeconomic development and transportation accessibility are generally negatively associated with village distribution, but in tourism-driven areas such as Dali and Lijiang, road improvements have facilitated protection and revitalization; and (5) historical and cultural factors, particularly proximity to nationally protected cultural heritage sites, contribute to spatial clustering and long-term preservation. The MGWR model achieves strong explanatory power (R2 = 0.555, adjusted R2 = 0.495) and outperforms OLS and standard GWR, confirming its suitability for analyzing the spatial mechanisms of traditional villages. Finally, the study offers targeted recommendations for the conservation and sustainable development of traditional villages in Yunnan. Full article
(This article belongs to the Special Issue Advanced Study on Urban Environment by Big Data Analytics)
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