Editorial on Urban Infrastructure and Resilient, Sustainable Buildings

1. Introduction

Urban infrastructures and buildings today face the intertwined pressures of extreme disasters, cascading effects, carbon constraints, and social uncertainty [1,2]. Addressing these challenges demands a technological, environmental, and societal synthesis that evolves beyond siloed fixes into integrated capabilities spanning design, operation, and governance [3,4]. This Special Issue brings together 12 papers organized around three foundational pillars of sustainable buildings and infrastructures: Intelligence [5,6], Decarbonization [7,8], and Resilience [9,10], each providing sharpened insights into how cities can harness digital sensing and twins, accelerate low-carbon adoption and community practices, and strengthen data governance, social responsibility, and spatial design to evolve under future challenges.

2. Intelligence: Smart-Sensing Digital Twins and Scalable Monitoring

This theme captures the shift from periodic inspection to continuous, explainable, and scalable monitoring. Huang et al. (contribution 1) present a deep learning framework based on Inception v3 that achieves high-accuracy corrosion classification for steel, offering a lightweight route to automated condition assessment. Yang et al. (contribution 2) integrate Building Information Modeling (BIM) at Level of Development (LOD) 400 with a digital twin and live Internet of Things (IoT) feeds to deliver real-time anomaly detection and dashboarding for a noise barrier tunnel. Jiang et al. (contribution 3) combine unmanned aerial vehicle (UAV)-borne Light Detection and Ranging (LiDAR) camera fusion with learning-based segmentation to recover bridge geometry at scale. Wang et al. (contribution 4) provide a review of wireless sensor networks for viaduct structural health monitoring (SHM). Together, these works sketch a new paradigm of multi-sensor intelligence, digital twins, and machine learning that closes the loop from sensing to action.

3. Decarbonization: Adoption Incentives and Community Practice

This theme examines the drivers and levers that turn carbon intent into measurable outcomes. Jin et al. (contribution 5) develop and validate an integrated Technology Acceptance Model and Technology Organization Environment (TAM-TOE) framework for hospital construction. Li et al. (contribution 6) provide a bibliometric analysis of human settlement improvement from 2012 to 2022. Gu et al. (contribution 7) classify and quantify resident engagement in sponge-style old community renewal, linking micro-level participation to performance and maintenance of low-impact development (LID) facilities. Collectively, these contributions form a complementary evidence chain across technology adoption, knowledge landscapes, and community governance.

4. Resilience: Data Governance Participation and Spatial Design

Resilience here spans engineering, data, social, and spatial dimensions. Xie et al. (contribution 8) trace how social risks in urban renewal evolve among stakeholders. Wu et al. (contribution 9) show that megaproject social responsibility behaviors improve performance, with resource integration capacity acting as a mediator. Hua et al. (contribution 10) link data governance capabilities to project organization resilience. Li and Lin (contribution 11) use multisource data and machine learning to map the impact of streetscape features on social sensing. Meknaci et al. (contribution 12) apply space syntax to reveal how connectivity and accessibility enhance sustainability in a Saharan city. The through line is clear: data governance, responsible action, participatory co-management, and spatial optimization must be intertwined to deliver comprehensive resilience.

5. Conclusions

Urban infrastructures and resilient, sustainable buildings are entering a decisive decade where digital intelligence, low-carbon pathways, and systemic resilience will no longer be optional, but essential. Looking ahead, four directions are particularly critical for advancing urban infrastructures and buildings. First, infrastructures across transport, energy, water, and buildings must be integrated to deliver systemic efficiency and resilience. Second, large-scale AI models and cross-modal learning should drive predictive maintenance and intelligent governance at the city scale. Third, low-carbon mechanisms must couple technology adoption with policy and economic incentives to secure tangible emission reductions. Finally, participatory and risk-sensitive governance needs to embed social responsibility and stakeholder co-management into urban renewal and megaprojects.