Urban Infrastructure and Resilient, Sustainable Buildings

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Architectural Design, Urban Science, and Real Estate".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 9436

Special Issue Editors


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Guest Editor
Department of Construction and Real Estate, School of Civil Engineering, Southeast University, Nanjing 210018, China
Interests: infrastructure resilience; sustainable city; low carbon building

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Guest Editor
Department of Civil and Environmental Engineering, University of Macau, Macau 999078, China
Interests: sustainable buildings; intelligent buildings

Special Issue Information

Dear Colleagues,

Global cities are increasingly confronting a barrage of natural disasters and man-made threats, stemming from the far-reaching impacts of climate change, rapid urbanization, and regional conflicts. Effectively addressing these multifaceted challenges and bolstering the resilience and sustainability of our built environment have emerged as paramount priorities. The compelling urgency of the development of resilient and sustainable infrastructures and buildings cannot be overstated.

This Special Issue is dedicated to propelling buildings, infrastructures, and cities towards heightened resilience and sustainability, arming them with the latest in cutting-edge research. We extend a warm invitation to scholars from across the globe to contribute innovative theoretical, methodological, and empirical research papers that may encompass a wide spectrum of themes, including, though not limited to, the conceptualization, interpretation, comparison, modeling, assessment, and analysis of urban infrastructure and resilient, sustainable buildings. We place a special emphasis on practical solutions that pave the way for the future development of cities and society.

We wholeheartedly welcome papers on the following and related topics including, but not limited to:

  1. Energy-efficient building solutions;
  2. Climate-resilient urban infrastructure;
  3. Sustainable building design and assessment;
  4. low-carbon buildings and cities;
  5. Innovative urban planning approaches;
  6. Sustainable materials and construction methods;
  7. Green spaces and biodiversity in built environment;
  8. Smart technologies for resilience and sustainability;
  9. Policy and governance strategies to promote sustainability;
  10. Enhancing the resilience of interdependent infrastructure systems;
  11. Disaster risk assessment of built environment.

Dr. Shenghua Zhou
Dr. Tiantian Gu
Dr. Mun On Wong
Guest Editors

Manuscript Submission Information

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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

  • sustainable cities
  • sustainable buildings
  • urban resilience
  • smart infrastructure
  • low-carbon buildings and cities
  • infrastructure resilience
  • interdependent infrastructure
  • low-carbon infrastructure
  • resilient buildings
  • sustainable built environment

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Published Papers (9 papers)

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Research

29 pages, 28502 KiB  
Article
Mapping the Impact of Spontaneous Streetscape Features on Social Sensing in the Old City of Quanzhou, China: Based on Multisource Data and Machine Learning
by Keran Li and Yan Lin
Buildings 2025, 15(9), 1522; https://doi.org/10.3390/buildings15091522 - 1 May 2025
Viewed by 222
Abstract
Streetscapes in old urban areas are not only an important carrier to show regional economies and city style, but also closely correlate to urban residents’ everyday life and the hustle and bustle in which they live. Nevertheless, previous studies have either focused on [...] Read more.
Streetscapes in old urban areas are not only an important carrier to show regional economies and city style, but also closely correlate to urban residents’ everyday life and the hustle and bustle in which they live. Nevertheless, previous studies have either focused on a few examples with low-throughput surveys or have lacked a specific consideration of spontaneous features in the data-driven explorations. Furthermore, the impact of spontaneous streetscape features on diversified social sensing has rarely been examined. This paper combined the mobile collection of street view images (SVIs) and a machine learning algorithm to calculate eight types of spontaneous streetscape elements and integrated two online platforms (Dianping and Sina Weibo) to map the distribution of economic vitality and social media perception, respectively. Then, through comparing multiple regression models, the impacts of the spontaneous streetscape characteristics on social sensing were revealed. The results include the following two aspects: (1) overall, the spontaneous streetscape features have a certain similarity in the impact on both dimensions of social sensing in Quanzhou, with significant clustering and transitional trends and strong spatial heterogeneity; and (2) specifically, the spontaneous streetscape elements can be divided into three categories, given the differentiated roles of significantly positive, negative, and polarizing impacts on the social sensing results. For example, proper use of open-interface storefronts, ads, and banners is consistent with the common suggestions, while the excessive pursuit of interface diversity and the use of cultural elements may bring an ambiguous effect. This paper provides a transferable analytical framework for mixed and data-driven sensing of streetscape regeneration and can potentially inspire related decisionmakers to adopt a more refined and low-cost approach to enhance urban vitality and sustainability. Full article
(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings)
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23 pages, 20311 KiB  
Article
Bridge Geometric Shape Measurement Using LiDAR–Camera Fusion Mapping and Learning-Based Segmentation Method
by Shang Jiang, Yifan Yang, Siyang Gu, Jiahui Li and Yingyan Hou
Buildings 2025, 15(9), 1458; https://doi.org/10.3390/buildings15091458 - 25 Apr 2025
Viewed by 257
Abstract
The rapid measurement of three-dimensional bridge geometric shapes is crucial for assessing construction quality and in-service structural conditions. Existing geometric shape measurement methods predominantly rely on traditional surveying instruments, which suffer from low efficiency and are limited to sparse point sampling. This study [...] Read more.
The rapid measurement of three-dimensional bridge geometric shapes is crucial for assessing construction quality and in-service structural conditions. Existing geometric shape measurement methods predominantly rely on traditional surveying instruments, which suffer from low efficiency and are limited to sparse point sampling. This study proposes a novel framework that utilizes an airborne LiDAR–camera fusion system for data acquisition, reconstructs high-precision 3D bridge models through real-time mapping, and automatically extracts structural geometric shapes using deep learning. The main contributions include the following: (1) A synchronized LiDAR–camera fusion system integrated with an unmanned aerial vehicle (UAV) and a microprocessor was developed, enabling the flexible and large-scale acquisition of bridge images and point clouds; (2) A multi-sensor fusion mapping method coupling visual-inertial odometry (VIO) and Li-DAR-inertial odometry (LIO) was implemented to construct 3D bridge point clouds in real time robustly; and (3) An instance segmentation network-based approach was proposed to detect key structural components in images, with detected geometric shapes projected from image coordinates to 3D space using LiDAR–camera calibration parameters, addressing challenges in automated large-scale point cloud analysis. The proposed method was validated through geometric shape measurements on a concrete arch bridge. The results demonstrate that compared to the oblique photogrammetry method, the proposed approach reduces errors by 77.13%, while its detection time accounts for 4.18% of that required by a stationary laser scanner and 0.29% of that needed for oblique photogrammetry. Full article
(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings)
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22 pages, 14232 KiB  
Article
Design and Validation of a Real-Time Maintenance Monitoring System Using BIM and Digital Twin Integration
by Seung-Won Yang, Yuki Lee and Sung-Ah Kim
Buildings 2025, 15(8), 1312; https://doi.org/10.3390/buildings15081312 - 16 Apr 2025
Viewed by 445
Abstract
This study presents a real-time monitoring system integrating Building Information Modeling (BIM) and digital twin technology to enhance maintenance efficiency and safety in urban infrastructure. Unlike conventional periodic inspections, which miss dynamic changes and increase costs, this system uses a BIM model at [...] Read more.
This study presents a real-time monitoring system integrating Building Information Modeling (BIM) and digital twin technology to enhance maintenance efficiency and safety in urban infrastructure. Unlike conventional periodic inspections, which miss dynamic changes and increase costs, this system uses a BIM model at LOD 400 for a solar-powered noise barrier tunnel integrated with the Wansan Tunnel in South Korea. It incorporates IoT sensor data, including vibration, tilt, light, air quality, and water detection, which are synchronized via the Autodesk Forge API, and WebSockets and visualized on a web-based dashboard. A demonstration from 22 October to 7 November 2024 confirmed that this system had stable data transmission, with light sensor rates exceeding 90%, and enabled the detection of anomalies such as irregular illuminance and structural shifts, thereby supporting informed maintenance decisions. While it is proven that BIM–digital twin integration improves NBT management, partial air quality data gaps highlight areas for refinement. This framework lays the groundwork for predictive maintenance through advanced analytics. Full article
(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings)
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26 pages, 2151 KiB  
Article
How to Foster Project Organization Resilience in the Construction Industry: The Role of Data Governance Capabilities
by Yuanyuan Hua, Manlin Kang, Hongjiang Yao and Yafan Fu
Buildings 2025, 15(8), 1219; https://doi.org/10.3390/buildings15081219 - 8 Apr 2025
Viewed by 267
Abstract
With the ongoing changes in global economic and social environments, project organization resilience has emerged as a core competency in addressing environmental uncertainty, thereby becoming a prominent research area within construction management. This resilience is intricately linked to data resources; however, construction enterprises [...] Read more.
With the ongoing changes in global economic and social environments, project organization resilience has emerged as a core competency in addressing environmental uncertainty, thereby becoming a prominent research area within construction management. This resilience is intricately linked to data resources; however, construction enterprises face systemic challenges in governance—fragmented data standards, siloed storage, and underutilized analytics—which limit their ability to translate data into crisis-responsive actions. Consequently, it is of paramount importance to investigate how data governance capabilities influence project organization resilience. This study initially identifies five dimensions of data governance capabilities within construction enterprises, spanning the three stages of planning, flow, and application: top-level design, data standard management, data collection, data storage, and data application. These dimensions are derived through a combination of literature review and expert interviews. Subsequently, this study establishes a theoretical model titled “Data Governance Capability—Project Organization Resilience”, exploring the relationships among these data governance capability dimensions and their correlations with project organization resilience. Data were collected through 142 valid questionnaires from practitioners in the Chinese construction industry and analyzed by the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The results indicate a significant relationship between data governance capabilities and project organization resilience, contributing to the research on the antecedents of the latter. This study offers a scale for construction enterprises to systematically assess data governance capabilities and provides guidance on enhancing organization resilience by progressively nurturing these capabilities. Full article
(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings)
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18 pages, 34409 KiB  
Article
A Deep Learning Framework for Corrosion Assessment of Steel Structures Using Inception v3 Model
by Xinghong Huang, Zhen Duan, Shaojin Hao, Jia Hou, Wei Chen and Lixiong Cai
Buildings 2025, 15(4), 512; https://doi.org/10.3390/buildings15040512 - 7 Feb 2025
Cited by 1 | Viewed by 862
Abstract
Corrosion detection plays a crucial role in the effective lifecycle management of steel structures, significantly impacting maintenance strategies and operational performance. This study presents a machine vision-based approach for classifying corrosion levels in Q235 steel, providing valuable insights for lifecycle assessment and decision-making. [...] Read more.
Corrosion detection plays a crucial role in the effective lifecycle management of steel structures, significantly impacting maintenance strategies and operational performance. This study presents a machine vision-based approach for classifying corrosion levels in Q235 steel, providing valuable insights for lifecycle assessment and decision-making. Accelerated salt spray tests were performed to simulate corrosion progression over multiple cycles, resulting in a comprehensive dataset comprising surface images and corresponding eight loss measurements. A comparative evaluation with other architectures, namely, AlexNet, ResNet, and VggNet, demonstrated that the Inception v3 model achieved superior classification accuracy, exceeding 95%. This method offers an effective and precise solution for corrosion evaluation, supporting proactive maintenance planning and optimal resource allocation throughout the lifecycle of steel structures. By leveraging advanced deep learning techniques, the approach provides a scalable and efficient framework for enhancing the sustainability and safety of steel infrastructure. Full article
(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings)
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29 pages, 4398 KiB  
Article
Classifying and Quantifying Resident Engagement in the Sponge-Style Old Community Renewal of China: An Analysis Using the Analytic Network Process–Preference Ranking Organization Method for Enrichment Evaluations II Method
by Tiantian Gu, Muhan Xie, Enyang Hao, Yongchao Wang and Shenghua Zhou
Buildings 2024, 14(12), 3773; https://doi.org/10.3390/buildings14123773 - 26 Nov 2024
Viewed by 798
Abstract
Resident engagement is highlighted as a crucial aspect that directly impacts the residents’ well-being of life in the process of sponge-style old community renewal (SOCR). However, there is a lack of in-depth study on exploring the classification of resident engagement clusters in the [...] Read more.
Resident engagement is highlighted as a crucial aspect that directly impacts the residents’ well-being of life in the process of sponge-style old community renewal (SOCR). However, there is a lack of in-depth study on exploring the classification of resident engagement clusters in the SOCR and developing a comprehensive evaluation system to measure this engagement. Therefore, this paper categorizes resident engagement into distinct clusters and develops an evaluation method for quantifying resident engagement in the SOCR. First, this study identified seven types of engagement clusters in the SOCR drawing from educational psychology and Arnstein’s citizen engagement ladder theory. Second, an evaluation indicator system with 5 primary indicators and 21 secondary indicators was developed through a literature review and expert interviews. Third, a hybrid evaluation method combining the Analytic Network Process (ANP) and Preference Ranking Organization Method for Enrichment Evaluations II (PROMETHEE II) was established to effectively quantify resident engagement in the SOCR. Finally, 16 typical communities from five Chinese cities were selected as study areas to examine resident engagement in the SOCR. The results demonstrated that the full engagement cluster achieved the highest scores at the individual level, while the non-engagement cluster recorded the lowest scores. At the city level, Shanghai attained the highest overall engagement score, whereas Chizhou recorded the lowest. Several strategies were proposed to improve resident engagement in the SOCR. This study not only contributes to the body of knowledge on resident engagement in the SOCR but also provides guidance for fostering resident engagement in sponge city construction. Full article
(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings)
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26 pages, 5527 KiB  
Article
Analysis of the Urban Form of Bechar through the Attributes of Space Syntax “for a More Sustainable City”
by Mohammed El Fatih Meknaci, Xingping Wang, Ratiba Wided Biara and Wiem Zerouati
Buildings 2024, 14(7), 2103; https://doi.org/10.3390/buildings14072103 - 9 Jul 2024
Cited by 2 | Viewed by 1839
Abstract
Located in the vast Algerian Sahara, Bechar has experienced over the years uncontrolled urban growth. It has evolved from a simple oasis and ksar (traditional settlement) to a city with a contrasting center and segregated outskirts. This growth has led to significant urban [...] Read more.
Located in the vast Algerian Sahara, Bechar has experienced over the years uncontrolled urban growth. It has evolved from a simple oasis and ksar (traditional settlement) to a city with a contrasting center and segregated outskirts. This growth has led to significant urban fragmentation that affected residents’ quality of life. This research uses space syntax theory to analyze Bechar’s urban configurations and their impact on functionality and sustainability. The study examines integration, connectivity, control, and intelligibility through axial maps and syntactic measures. Findings reveal that areas with high integration show better accessibility and reduced vehicle reliance, while segregated areas face accessibility challenges and limited services. Global integration values range from −1 to 1.192, averaging at 0.767, which indicates different accessibility among neighborhoods. These insights are crucial to identify areas where sustainable urban planning can mitigate adverse effects and enhance city efficiency. We created an axial map using DepthmapX v0.8.0 software and a modified digital QGIS map to collect data and measure Bechar’s urban properties. The methodology we used translates social behaviors into spatial representations, generating interpretative models for social and spatial phenomena. This article provides valuable information on the infrastructure and service needs, guiding strategic resource allocation. The proposed urban design strategies include urban canopies and optimized building ratios to reduce energy consumption and promote sustainability. To conclude, we recommend practical solutions to enhance the sustainability and functioning of urban areas similar to Bechar. Full article
(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings)
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27 pages, 1655 KiB  
Article
Exploring the Evolution Mechanisms of Social Risks Associated with Urban Renewal from the Perspective of Stakeholders
by Hong Xie, Lei Zhang, Peng Cui, Jingfeng Yuan and Qiming Li
Buildings 2024, 14(5), 1470; https://doi.org/10.3390/buildings14051470 - 18 May 2024
Cited by 6 | Viewed by 1579
Abstract
The urban renewal (UR) process involves various stakeholders and related activities, and the various risks arising from this endeavor can affect these stakeholders. Additionally, the impact of adverse factors such as policy discontinuity and inequitable distribution of benefits among stakeholders can easily result [...] Read more.
The urban renewal (UR) process involves various stakeholders and related activities, and the various risks arising from this endeavor can affect these stakeholders. Additionally, the impact of adverse factors such as policy discontinuity and inequitable distribution of benefits among stakeholders can easily result in collective tensions or conflicts, as well as the gradual emergence of potential social frictions and confrontations. These social risks (SRs) not only impede the smooth execution of urban renewal projects but also pose challenges to social harmony and stability. Hence, to mitigate and control the SRs in the UR process (URSRs) and ensure the successful implementation of effective and sustainable UR projects, it is of paramount importance to gain a comprehensive understanding of the occurrence and evolution mechanisms of these SRs. Although existing studies have touched upon the influence of stakeholder conflicts on URSRs, there remains a lack of systematic examination of the evolution mechanisms of these risks from the perspective of stakeholder theory. The resulting fragmented and specialized comprehension of URSRs has hindered the effectiveness of risk governance strategies. This study adopts stakeholder theory to analyze the potential sources of risk throughout the entire UR process. By considering the conflicts of interests among stakeholders, a systematic analysis of the evolution mechanisms of URSRs is explored and targeted governance recommendations for URSRs are proposed. Full article
(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings)
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29 pages, 1770 KiB  
Article
A Bayesian Network Model of Megaproject Social Responsibility Behavior and Project Performance: From the Perspective of Resource-Based Theory
by Yuhua Wu, Zhao Zhou, Linlin Xie, Bo Xia and Mian Huang
Buildings 2024, 14(4), 1143; https://doi.org/10.3390/buildings14041143 - 18 Apr 2024
Viewed by 1347
Abstract
Megaproject Social Responsibility (MSR) is widely acknowledged as contributing to project performance. However, the effect of Megaproject Social Responsibility Behavior (MSRB) implemented by organizations participating in construction on project performance remains a subject of considerable debate, and the intrinsic mechanism of MSRB’s effect [...] Read more.
Megaproject Social Responsibility (MSR) is widely acknowledged as contributing to project performance. However, the effect of Megaproject Social Responsibility Behavior (MSRB) implemented by organizations participating in construction on project performance remains a subject of considerable debate, and the intrinsic mechanism of MSRB’s effect on the performance of megaprojects has not been elucidated. Therefore, this study employs resource-based theory to investigate the mechanism underlying MSRB’s effect on project performance, taking into account both internal and external social capital as well as resource integration capacity as pivotal influences. Drawing on sample data from 206 experienced project managers across the various parties involved, this study develops a Bayesian network model to elucidate the MSRB effect mechanism. Through inference and sensitivity analysis, this study discovers variations in the enhancement effects across the four dimensions of MSRB on project performance. Notably, a combination strategy yields superior enhancement effects. Furthermore, when project performance is suboptimal, resource integration capacity emerges as a significant mediator between MSRB and project performance. Conversely, at high levels of project performance, MSRB directly contributes to enhancing project outcomes. The findings of this study offer valuable insights for the governance of MSR and the enhancement of project performance in megaprojects. Full article
(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings)
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