This article, via empirical studies, investigates the influences of facility accessibility, facility correlation, and resident satisfaction on urban spatial quality. It is discovered that these three elements are positively correlated with urban spatial quality. Excellent facility accessibility and rational layout can elevate urban spatial quality, and resident satisfaction reflects the outcome of environmental optimization. On this basis, this article puts forward strategies of intensifying infrastructure construction, using multi-source data to optimize the transportation system, implementing humanistic care and promoting community interaction, promoting digital and intelligent management of the city, and paying attention to the cultural aesthetics of the city, with the aim of offering theoretical support and practical guidance for enhancing urban spatial quality, facilitating sustainable urban development and the improvement of residents’ quality of life.

The revitalization and renewal of existing urban space is a primary objective in the redevelopment of high-density transit-oriented development (TOD) areas. In this context, offering incentive zoning bonuses is a critical tool for optimizing urban space. However, in some subway-adjacent plots with high building densities, traditional incentive zoning methods face limitations due to insufficient horizontal space. These areas increasingly rely on multi-ground public spaces to balance density with public services. This study investigates new methods of incentive zoning between commercial areas and public spaces in multi-ground public spaces within subway-adjacent plots, using 33 rail transit complexes in Shanghai, China, as the research subject. The findings are presented in the form of visual guidelines to provide guidance on architectural control, with the goal of enhancing the quality of urban public spaces. In this research, a multiple linear regression model is employed, using GNCS_AR (the ratio of ground non-commercial stay to area), which captures both efficiency and equity in public space quality, as the dependent variable. A model is developed in SPSS, incorporating independent variables such as TCA (total commercial area), POS (public open space area), PIS (public indoor space area), and MGZFs (multi-ground zoned floors). This model provides a framework for developers to manage and control public space in multi-ground settings within rail transit complexes. Research has found that MGZFs alone cannot be included as the independent variable in the model, as their absence leaves the model unable to explain three-dimensional spaces. However, incorporating the ratio of RIOPS (the ratio of indoor to outdoor public space) to MGZFs significantly improves the model’s correlation and explanatory capacity. The resulting model demonstrates that, under different POS and MGZF tiers, the influence of PIS and TCA on public space quality varies. Using a typological approach, the study categorizes these complexes into five tiers based on POS and MGZFs. Within the same tier, changes in PIS and TCA types lead to variations in public space quality. The empirical results are translated into diagrams that link data, forms, and indicators to guide the development of three-dimensional spaces. These diagrams, which can be named visual guidelines, provide practical guidelines for optimizing public spaces in these subway-adjacent plots.

Against the backdrop of Shenzhen’s high-density urban environment, the multifunctional design of water purification plants offers dual benefits: providing residents with urban green spaces while simultaneously mitigating NIMBY sentiments due to their inherent characteristics. Unlike traditional urban development, Shenzhen’s water purification plants integrate into residents’ daily lives. Therefore, optimizing the built environment and road network structure to enhance residents’ perceptions of proximity benefits while reducing NIMBY (Not In My Backyard effect) sentiments holds significant implications for the city’s sustainable development. To address this question, this study adopted the following three-step mixed-methods approach: (1) It examined the relationships among residents’ YIMBY (Neighboring Benefits Effect) and NIMBY perceptions, perceptions of park spaces atop water purification plants, and perceptions of accessibility through questionnaire surveys and structural equation modeling (SEM), establishing a scoring framework for comprehensive YIMBY and NIMBY perceptions. (2) Random forest models and Shapley Additive Explanations (SHAP) analysis revealed nonlinear relationships between the built environment and composite YIMBY and NIMBY perceptions. (3) Spatial syntax analysis categorized the upgraded road network around the water purification plant into grid-type, radial-type, and fragmented-type structures. Scatter plot fitting methods uncovered relationships between these road network types and resident perceptions. Finally, negative perceptions were mitigated by optimizing path enclosure and reducing visual obstructions around the water purification plant. Enhancing neighborhood benefits—through improved path safety and comfort, increased green spaces and resting areas, optimized path networks, and diversified travel options—optimized the built environment. This approach proposes design strategies to minimize NIMBY perceptions and maximize YIMBY perceptions.

Under the combined pressures of extreme rainfall and rapid urbanization, urban waterlogging has become increasingly severe. As high-density and low-income settlements, urban villages are particularly vulnerable. Taking the "9·7" extreme rainstorm event in Shenzhen as a case, this study analyzes 623 urban-village study units across the Longgang River and Shenzhen River basins to identify urban-form-related factors and empirical thresholds associated with waterlogging risk under an extreme rainfall scenario. Specifically, we focus on the dominant role of the topographic low-lying effect and the amplifying effect of street-canyon characteristics on the vulnerability of urban villages. By integrating multi-source data and constructing a multi-scale buffer analysis framework, we quantify the spatial contrasts between urban villages and their surrounding environments. An XGBoost model, combined with SHAP analysis and partial dependence plots (PDPs), is used to interpret the contribution of each factor, nonlinear thresholds, and interaction effects. The results show that: (1) the topographic low-lying effect exhibits the strongest explanatory contribution and presents a clear threshold-switch pattern, with absolute elevation as the leading factor; (2) within a 0-400 m range, urban villages form significant morphological contrasts with their surroundings, constituting a risk "vulnerability ring"; (3) street-canyon indicators are more informative than traditional density indicators, highlighting the critical role of micro-scale urban form in regulating runoff pathways; and (4) maintaining the sky view factor (SVF) within the range of 0.3-0.55 is associated with lower waterlogging risk. Overall, this study identifies urban-form-related factors, nonlinear response patterns, and empirical risk thresholds of urban-village waterlogging, providing a scientific basis for targeted resilience enhancement.

Rapid urbanization-induced extreme rainstorms severely disrupt social functions. Previous research often focused on “de-densification” strategies, which are difficult to adapt to high-density Sponge City Stormwater Management Units (SMUs) that carry core development functions. This study uses Shenzhen as a case study, utilizing Keep movement big data as a “social sensor” for system function perception and introducing the Socio-Ecological-Technological Systems (SETS) theory to construct a “recovery (RCN)–resistance (MI)” binary assessment framework. Through systematic clustering and hierarchical regression models, the driving mechanisms of blue landscape patterns, topography, road networks, and the built environment on social behavioral resilience are systematically parsed. The results show: (1) Road network morphology dominates resistance, while multi-dimensional elements collaborate for recovery. Resistance (MI) is primarily dominated by macro road network detour resistance (TPD2000, β = 0.956), while recovery depends on the synergistic support of blue space interspersion (Blue_IJI), topography, and micro-circulation road networks. (2) Green infrastructure fails in the model due to efficiency bottlenecks, empirical evidence of weakened regulation caused by green space fragmentation in ultra-high-density environments. (3) Low-density, eco-centric built environments provide dual synergistic gains for resilience. Based on this, a “Bidirectional Socio-Ecological Resilience Needs Pyramid” model is constructed, identifying four governance types such as the “Synergistic Balanced Type”. This study provides a quantitative basis for the transition from administrative control to precise morphological governance in high-density cities.