Submit to Special Issue Submit Abstract to Special Issue Review for Buildings Propose a Special Issue

Journal Menu

Journal Browser

Urban Infrastructure and Resilient, Sustainable Buildings

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Published Papers

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 10921

Share This Special Issue

Special Issue Editors

Dr. Shenghua Zhou

E-Mail Website
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

Dr. Tiantian Gu

E-Mail Website
Guest Editor

School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, China
Interests: community resilience; smart communities; urban renewal; risk assessment; public engagement
Special Issues, Collections and Topics in MDPI journals

Dr. Mun On Wong

E-Mail Website
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:

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

Dr. Shenghua Zhou
Dr. Tiantian Gu
Dr. Mun On Wong
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 100 words) can be sent to the Editorial Office for announcement on this website.

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

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (11 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

Jump to: Review

18 pages, 1611 KiB

Open AccessArticle

A Bibliometric Analysis of Research on Human Settlements Improvement Based on CNKI and Web of Science

by Chenxi Li, Jinfeng Miao, Xuan Zhai and Qiao Liu

Buildings 2025, 15(11), 1805; https://doi.org/10.3390/buildings15111805 - 24 May 2025

Viewed by 148

Abstract

In the context of rural revitalization, scientific and efficient improvement of the human settlement environment is of great practical significance to improve the quality of life of farmers as well as to promote modern rural construction. To understand the research status and trends of human settlement environment improvement, the paper visually analyzed the relevant literature from 2012 to 2022 based on CNKI and the Web of Science database with the help of CiteSpace software(developed by Chaomei Chen, Drexel University, Philadelphia, PA, USA) (v6.2.r2). The results show the following: (1) the research literature on human settlement environment improvement has undergone three stages of slow growth, steady growth, and explosive growth; (2) many countries and institutions have published research on the improvement of human settlement environment, forming a close cooperative relationship; (3) three research hotspots have been formed: the concept and classification of the human settlement environment, the improvement path of the human settlement environment, and the evaluation method of the human settlement environment; and (4) waste management and green space are the frontier issues in the field of human settlement environment improvement. The subsequent research on the improvement of human settlement environments should strengthen the breadth and depth of research, improve the evaluation index system, innovate research methods, and build interdisciplinary integration, to provide a perfect research paradigm for research on the improvement of human settlement environments in the future. Full article

(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings)

► Show Figures

Figure 1

29 pages, 28502 KiB

Open AccessArticle

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 326

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 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)

► Show Figures

Figure 1

23 pages, 20311 KiB

Open AccessArticle

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 394

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 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)

► Show Figures

Figure 1

22 pages, 14232 KiB

Open AccessArticle

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 630

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 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)

► Show Figures

Figure 1

26 pages, 2151 KiB

Open AccessArticle

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

Cited by 1 | Viewed by 369

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 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)

► Show Figures

Figure 1

18 pages, 34409 KiB

Open AccessArticle

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 944

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. 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)

► Show Figures

Figure 1

29 pages, 4398 KiB

Open AccessArticle

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 840

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 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)

► Show Figures

Figure 1

26 pages, 5527 KiB

Open AccessArticle

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 1967

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 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)

► Show Figures

Figure 1

27 pages, 1655 KiB

Open AccessArticle

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 7 | Viewed by 1630

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 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)

► Show Figures

Figure 1

29 pages, 1770 KiB

Open AccessArticle

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 1391

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 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)

► Show Figures

Figure 1

Review

Jump to: Research

22 pages, 2339 KiB

Open AccessReview

Urban Viaduct Structural Health Monitoring: A Review of Wireless Sensor Approaches

by Tianli Wang, Tong Cui, Xin Qi and Xintao Huan

Buildings 2025, 15(10), 1619; https://doi.org/10.3390/buildings15101619 - 11 May 2025

Viewed by 350

Abstract

Urban viaducts have been extensively built in large cities due to traffic pressure on main roads. Although urban viaducts provide relief and reduce traffic, they also pose potential threats to citizens’ safety due to the possibility of collapse. However, most collapses do not happen instantly. Structural health monitoring (SHM) systems can effectively detect structural damage to prevent collapses; however, they are not widely deployed due to the high cost of sensor installation. With wireless sensor technology thriving due to its accuracy and cost-efficiency, the wireless monitoring of massive urban viaducts has become possible. In this paper, we review the full-chain methods of employing wireless sensor technology for urban viaduct structural health monitoring. By proposing a general wireless structural health monitoring approach as a framework, we first review the sensor types and wireless transmission technologies, then the data processing and modal identification methods, and finally the damage detection methods. This paper aims to provide a full-chain review of the mainstream methods in wireless sensor approaches for the SHM of urban viaducts. Full article

(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings)

► Show Figures

Journal Menu

Journal Browser

Urban Infrastructure and Resilient, Sustainable Buildings

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (11 papers)

Research

Review

Further Information

Guidelines

MDPI Initiatives

Follow MDPI