Environmental justice advocates that all people are protected from disproportionate impacts of environmental hazards. Despite this ideal aspiration, social and environmental inequalities exist throughout greater Los Angeles. Previous research has identified and mapped pollutant levels, demographic information, and the population’s socioeconomic status and health issues. Nevertheless, the complex interrelationships between these factors remain unclear. To close this knowledge gap, we first measured the spatial centrality using sDNA software. These data were then integrated with other socioeconomic and health data collected from CalEnvironScreen, with census tract as the unit of analysis. Finally, structural equation modeling (SEM) was executed to explore direct, indirect, and total effects among variables. The results show that the White population tends to reside in the more segregated areas and lives closer to green space, contributing to higher housing stability, financial security, and more education attainment. In contrast, people of color, especially Latinx, experience the opposite of the environmental benefits. Spatial centrality exhibits a significant indirect effect on environmental justice by influencing ethnicity composition and pollution levels. Moreover, green space accessibility significantly influences environmental justice via pollution. These findings can assist decision-makers to create a more inclusive society and curtail social segregation for all individuals.

Extensive studies have demonstrated the relationship between static street networks and dynamic pedestrian movement. Street vendors temporarily appear in a vibrant space, closely engaging with numerous pedestrians. Is street vending distribution related to street network configuration? And if so, in what ways? This study investigates the heterogeneous relationships between pedestrians, vendors and the urban and suburban places they inhabit in Yuncheng by contrasting two different types of pedestrian-driven maps. The vending distribution map was identified via semi-structured interviews with urban managers (n = 11) in 2017. The spatial network configuration was examined through space syntax segment angular analysis, containing Integration, Choice and Combined Centrality properties at macro-, meso- and micro-scales. By overlapping the distribution map to the syntactic maps in the Quantum Geographic Information System (QGIS) platform, our results show that street vending distribution is most related to the Choice property at the meso-scale. Using semi-structured interviews (n = 53) and observations at two specific sites, we further found relationships tend to be opposed in urban and suburban areas. The study provides an alternative approach to integrating quantitative and qualitative data, expanding the theoretical and empirical understanding of spatial configuration and urban street activities related to walking and vending. This understanding has the potential to contribute to the design of more liveable street spaces.

With the acceleration of urbanization and the continuous expansion of building stock, building maintenance plays a critical role in ensuring structural safety, extending service life, and promoting sustainable development. In recent years, the application of artificial intelligence (AI) in building maintenance has expanded significantly, markedly improving detection accuracy and decision-making efficiency through predictive maintenance, automated defect recognition, and multi-source data integration. Although existing studies have made progress in predictive maintenance, defect identification, and data fusion, systematic quantitative analyses of the overall knowledge structure, research hotspots, and technological evolution in this field remain limited. To address this gap, this study retrieved 423 relevant publications from the Web of Science Core Collection covering the period 2000–2025 and conducted a systematic bibliometric and scientometric analysis using tools such as bibliometrix and VOSviewer. The results indicate that the field has entered a phase of rapid growth since 2017, forming four major thematic clusters: (1) intelligent construction and digital twin integration; (2) predictive maintenance and health management; (3) algorithmic innovation and performance evaluation; and (4) deep learning-driven structural inspection and automated operation and maintenance. Research hotspots are evolving from passive monitoring to proactive prediction, and further toward system-level intelligent decision-making and multi-technology integration. Emerging directions include digital twins, energy efficiency management, green buildings, cultural heritage preservation, and climate-adaptive architecture. This study constructs, for the first time, a systematic knowledge framework for AI-enabled building maintenance, revealing the research frontiers and future trends, thereby providing both data-driven support and theoretical reference for interdisciplinary collaboration and the practical implementation of intelligent maintenance.

Open spaces in housing estates are crucial for residents’ physical and mental well-being, especially when access to other public spaces is restricted (e.g., during a pandemic). While existing studies focus on public spaces, less is known about how residential landscapes, particularly in gated estates, influence outdoor activities. This study investigates the spatial logic behind the distribution of standing, sitting and social interaction within six pairs of gated and non-gated housing estates in Wuhan. Using space syntax analysis and zero-inflated negative binomial regression, we explore how the spatial configuration influences the incidence of outdoor activities in gated and non-gated estates. The findings suggest that spatial attributes not only significantly explain where activities occurred but also where they did not. More importantly, we found distinct differences between the two types: non-gated estates were more responsive to design, with more spatial factors significantly predicting activities simultaneously, whereas in gated compounds, only a few factors had a significant impact. Critical factors of outdoor activities include seating provision, convex area, perimeter enclosure, and spatial accessibility. These findings contribute to the theoretical understanding of spatial dynamics in residential environments and provide practical insights for urban design and residential planning.