The COVID-19 pandemic constituted a profound disruption to urban life worldwide, sharply altering social practices, economic activity and demographic dynamics. While many studies have examined specific short-term consequences of the pandemic, comparatively little attention has been paid to how its effects interacted with other simultaneously unfolding crises and how disruptions might translate into permanent effects, embedded into a larger systemic conceptualization. This Special Issue addresses this gap by situating the pandemic within a broader polycrisis context, in which long-term structural stresses and fast-moving triggers intersect across economic, social, demographic and political systems. Drawing on systems thinking and the emerging polycrisis framework, we conceptualize how pandemic-induced changes in three urban domains—economic restructuring, demographic and migration shifts, and housing market transformations—have produced complex and uneven community-level effects. We further highlight how modes of policy and governance response have shaped outcomes, noting that actions taken to mitigate immediate impacts have often reinforced underlying systemic stresses or generated new risks. The contributions to this Special Issue present empirical evidence from cities across the Global North, illustrating both shared dynamics and diverse local trajectories. Together, these studies provide a foundation for understanding how crises may act as catalysts, accelerators or turning points in urban development. They underscore the need for analytical and policy approaches capable of addressing interconnected risks and supporting socially cohesive, resilient and sustainable urban futures in an era where polycrisis is becoming the new normal.
Graph-based GIS workflow is a relevant tool to urban planning and governance, yet most operational accessibility tools still rely on flat or Euclidean representations which can overestimate local dynamics in cities shaped by complex topography and fragmented urban forms. This limitation is especially critical at the neighborhood scale, where short walking trip structure everyday access to opportunities and services. This paper presents an original algorithm to delineate neighborhood scale planning units through the integration of slope-sensitive, territorial barriers, and urban morphology into isochrone modeling. The method structures a barrier-aware pedestrian graph on the block fabric, assigns edge costs from topography, and produces dual time–distance isochrones through an iterative seeding procedure to identify shortest walkable paths. A subsequent classification stage generates a typology of accessibility polygons based on area, population, radii, elevation, and administrative overlap. Applied to the municipality of São Paulo, Brazil, the framework generated 639 neighborhood scale isochrones and demonstrates that a 10-min or 800-m walking threshold does not correspond to a uniform spatial scale once topography and territorial discontinuities are explicitly incorporated. By analytically associating isochrones with transitional areas, the model reconceptualizes neighborhoods as flexible spatial perimeters rather than fixed administrative units, allowing their limits to be refined through public governance or participatory planning processes. In doing so, the study shifts isochrones from isolated accessibility outputs to a citywide system of planning-oriented units and offers a transferable geospatial computational framework for capturing local urban dynamics and supporting evidence-based active mobility and neighborhood planning in complex urban environments.
Inter-city cooperation has become a central institutional framework for city-regional development, yet its implications for cultural-symbolic connectivity remain underexplored. Drawing on insights from the policy mobilities literature, this study conceptualizes inter-city cooperation as an institutionalized relational infrastructure that shapes cultural-symbolic mobility within an uneven urban hierarchy. Using data from 41 cities in China's Yangtze River Delta (YRD), we measure cultural-symbolic flows with 250,616 place-name POIs and cooperation intensity with 247,035 government-reported cooperation events identified through natural language processing (NLP). The results show that stronger cooperation is positively associated with greater cultural-symbolic connectivity, operating through strengthened investment linkages, population mobility, and collaborative knowledge innovation. This association is more pronounced among non-adjacent cities, across metropolitan boundaries, and in relationships involving peripheral and non-metropolitan cities. These findings suggest that cultural-symbolic mobility within city-regions is shaped not merely by proximity or market forces but also by formal cooperation arrangements, which foster more inclusive regional integration.
Amid soaring housing prices and increasing social stratification, issues of housing equity in Chinese cities have become progressively prominent. Previous studies have mostly focused on the formal equity of spatial balance, while neglecting substantial disparities in urban facility accessibility and time costs across social groups. From the perspective of vertical equity, this study introduces the Matthew Effect to examine how the accumulation of socioeconomic advantages intensifies spatial differentiation and the unequal distribution of housing resources, revealing structural inequality among income groups in urban space. Using Nanjing as a case study, this research establishes a time-based evaluation system of urban facility accessibility and applies the multiscale geographically weighted regression (MGWR) model to analyze the spatial heterogeneity of housing prices. Integrating the Theil index with spatial match analysis, it further assesses the vertical equity of facility resource accessibility across different income levels. The results reveal a distinct concentric spatial structure of housing prices: high-income groups cluster in core areas with convenient transportation and abundant educational and environmental resources, while low-income groups are marginalized to peripheral zones with higher commuting costs and limited facilities. Differences in time accessibility to urban facilities further amplify price spillover effects in core areas, aggravating vertical inequity in the housing market. By integrating temporal accessibility analysis with multi-scale spatial modeling, this study advances the theoretical and methodological framework of housing equity and proposes a vertical-equity-oriented housing resource optimization strategy to promote balanced urban facility allocation, prevent resource over-concentration, and foster socially integrated urban development.
As AI becomes more embedded in urban systems, the demand for data centers continues to rise. This study analyzes 212 data centers in the U.S., focusing on those operated by major ICT enterprises. We examined key site-selection factors using clustering, suitability scoring, graph-based network analysis, and conditional logistic regression. K-means was selected for clustering. Variables were grouped into environmental and locational site-level factors to generate separate suitability indices. To identify siting determinants, we then estimated conditional logistic regression models, comparing each data center against spatially comparable control locations. The results highlight the complexity of selecting a site for a data center. In general, data centers exhibit spatial agglomeration and gain operational advantages from economies of scale. Clustering analysis grouped sites into six categories, each reflecting distinct locational and environmental patterns. The graph-based network analysis further illustrates the trade-offs companies must make between environmental suitability and operational site-level advantages. Regression results revealed that land use structure, particularly land use diversity and was the most powerful determinant of data center siting. Infrastructural factors, including substation density and proximity to primary roads, as well as the concentration of IT workers, also exhibited strong positive effects. Among environmental factors, lower wind speeds and PM2.5 concentrations positively influenced data center siting, while state-level policy incentives remained statistically insignificant. Our findings highlight the distinctive infrastructural characteristics of these facilities. Acknowledging their widespread operational footprint across diverse urban landscapes, planners must proactively engage with the physical and spatial dimensions of digital infrastructure.
Nonlinear relationships between public space recreational services (PSRS) and mental well-being remain unclear. This study aimed to examine the nonlinear relationships between individual and overall PSRS and mental well-being, and to explore the mediating roles of passive exposure (objective and subjective indicators of air pollution, meteorological conditions, and noise) and active exposure (physical activity). In Shanghai, we assessed the mental well-being of 1545 residents using the WHO-5. A systematic PSRS evaluation framework was developed, integrating objective PSRS (objective accessibility, objective availability, and objective attractiveness) and subjective PSRS (perceived accessibility and perceived attractiveness). Restricted cubic spline (RCS) analysis investigated nonlinear relationships between individual PSRS indicators and mental well-being. To assess the nonlinear relationship between overall PSRS and mental well-being and identify key indicators, we applied weighted quantile sum (WQS) regression, quantile-based g-computation (Qgcomp), and Bayesian kernel machine regression (BKMR). Mediation analysis used structural equation models (SEMs) incorporating both linear and quadratic terms of the overall PSRS index. The results suggested that (1) ND, WA, PAA, SAT, PA, and BD exhibited significant nonlinear relationships with mental well-being; (2) overall PSRS showed a nonlinear relationship peaking at the 50th percentile, and CL, IRF, PA, FAPS, WA, and AEST were identified as key indicators; and (3) objective passive exposure, subjective passive exposure, and the pathway from subjective passive exposure to active exposure showed significant indirect effects in the nonlinear PSRS–mental well-being relationship. These findings provide insights into optimizing PSRS planning and management to improve residents' mental well-being.
Against the combined pressures of climate warming and high-density urbanization, urban space is expected to mitigate heat while remaining supportive of everyday outdoor activity. Yet morphology that favors cooling may not necessarily favor jogging. Previous studies have linked LCZs to physical activity and evaluated how heat-mitigation strategies affect activity-related outcomes, but limited evidence identifies which urban-form parameters and value ranges can jointly support lower surface temperature and higher recorded jogging activity across different LCZ types. Using the urban area within Shanghai's Outer Ring, this study integrates jogging trajectories, land surface temperature (LST), and two- and three-dimensional (2D/3D) urban-form indicators within an LCZ framework. A workflow integrating random forest (RF), SHapley Additive exPlanations (SHAP), and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to identify shared key factors, characterize nonlinear responses, derive joint favorable ranges, and search for dual-objective solutions. Results show that shared morphological factors exhibit LCZ-specific and nonlinear relationships with mean LST and jogging distance. Vegetation-related factors show relatively consistent synergies across several LCZ types, whereas 3D form and accessibility-related factors display stronger interval sensitivity. Pareto fronts further reveal substantial differences in trade-off structure and parameter combinations across LCZs. High-density types show stronger dependence on coordinated multivariable adjustment, whereas open types are more sensitive to the configuration and proximity of blue-green spaces. The resulting LCZ-specific parameter ranges and Pareto-efficient configurations provide LCZ-specific planning references for coordinating surface-heat mitigation and jogging support in dense urban areas.
Environmental regulation is key to sustainable development, yet its impact on societal wellbeing remains underexplored. This study uses prefecture-level panel data from China (2000−2022) to examine how environmental regulations, both formal and informal, affect wellbeing across cities with varying economic development. Our findings show: (1) formal regulation does not typically enhance wellbeing, while informal regulation positively affects all cities. (2) The impact of formal regulation depends on a city's per capita GDP, supporting the “Porter Hypothesis” in wealthier cities, where formal regulations improve wellbeing, while the opposite occurs in poorer cities. (3) The moderating roles of industrial structure upgrading and employment are identified: they amplify the positive effect of formal regulation in wealthier cities but exacerbate its negative effect in poorer cities. For informal regulation, these two factors consistently serve as positive moderators across all city groups, reinforcing its beneficial effect on wellbeing. This study sheds light on the nuanced role of environmental regulation in promoting sustainable wellbeing in urban contexts.
Understanding bicycle commuting determinants is of critical importance in promoting sustainable mobility and effective transportation infrastructure planning. Using a nationwide dataset integrating the U.S. Environmental Protection Agency's Smart Location Database (SLD) and the American Community Survey (ACS), this research examines determinants of bicycle commuting in 1036 Census block groups in 41 U.S. states and 180 counties by combining built-environment, socioeconomic, and regional predictors in a four-model analytical framework. The analysis uses Ordinary Least Squares (OLS), Binary logistic regression (BLR), Generalized Linear Model (GLM), and a Linear Mixed-Effects Model (LMM) to describe both the probability and the degree of bicycle commuting. The OLS outcome indicates that transit frequency, population density, and educational attainment positively increase bicycle commute share, whereas distance to transit decreases bicycle commute share, and walkability shows a positive and statistically significant association with bicycle commuting. The BLR shows evidence of an increase in the odds of any bicycle commuting by 79% with a one-standard deviation increase in education and of low-accessibility areas having odds of bicycle commuting 62% lower than those of high-access areas. According to the GLM results, cyclists traveling in low-accessibility neighborhoods have about 20% longer commute durations. The LMM indicates a great deal of regional heterogeneity, with between-county differences accounting for 17% of the variance in bicycle share. Bicycle share is substantially increased by network connectivity and transit frequency. Together, the results indicate that compact and accessible urban structure, higher walkability, frequent transit service, and multimodal accessibility are significant bicycle commuting stimulators, and regional context plays a significant role in explaining between-county variation of bicycle commuting.
While internationally condemned, residents of informal settlements around the world continue to face the threat of eviction and displacement. In Asian cities, neoliberal urban development policy has been identified as a key driver of development-inducted displacement. Through the mapping of informal settlement displacement in three megacities in Asia, this paper investigates the spatial and temporal patterns of such displacement in a comparative way. Complemented by policy analysis, the displacement of informal settlements is analysed through trends in the annual distribution of displacement, the spatial concentration around central business areas and waterfronts, their post-demolition land-use, and the scale of individual demolitions. While practices of slum clearance and urban renewal in the three case study cities are all informed by neoliberal urban planning policy, this paper finds that the governance and finance arrangements characterizing each city have a clear impact on the spatiality of informal settlement displacement.
As global shocks become more frequent, strengthening the economic resilience of cities has become a central concern for sustainable urban development and governance. While economic and institutional conditions are widely acknowledged, the role of cultural factors in shaping cities' economic resilience remains underexplored in urban studies and policy debates. This study develops a global city-level gross domestic product (GDP) dataset for 7652 cities across 177 countries by combining monthly nighttime light data with a two-stage machine learning approach. Random forest is first employed in response to the post-2020 shock period, followed by XGBoost to generate high-frequency GDP estimates. Using these data, we evaluate cities' economic resistance, recoverability, and overall resilience to a series of shocks after 2020. Leveraging Hofstede's individualism index and applying OLS regressions with instrumental variable techniques, our results show that individualism has a significant negative effect on all three resilience dimensions. The negative association is more pronounced for recoverability than for resistance. Importantly, strong government regulation and robust infrastructure help to offset this adverse effect. These findings suggest that cultural orientation matters not only for how cities absorb shocks, but also for how effectively they coordinate recovery. By bringing culture into the analysis of global cities' economic resilience, this study extends existing research beyond material and institutional explanations and highlights the importance of governance capacity and infrastructure in culturally diverse contexts.
As cities grapple with eroding governing capacity and the resulting governance gap, prominent place-based foundations have engaged more directly in urban governance and development. Yet extant scholarship has not systematically examined what it means to substantively fill the governance gap through foundation-driven urban development, nor how specific process design choices shape the outcomes of such development. This research posits that filling the governance gap requires the development and institutionalization of both substantive capacity—new knowledge, ideas, and practices—and relational capacity—enduring relationships and institutional partnerships. Using negotiation and collaborative planning theories, this research analyzes how the Lyndhurst and Kresge Foundations' process design choices corresponded to the outcomes of their urban development efforts in Chattanooga (TN) and Detroit (MI), respectively. By integrating content analysis, non-participant observation, and semi-structured interviews, this paper finds that whether foundation-driven urban development produces the outcomes required to fill the governance gap hinges on the specific process design choices that foundations make about interests, coalitions, joint inquiry, and planning capacity. Lyndhurst's broad-based engagement enabled the incorporation of the resulting plans and strategies into formal plans and policies, while building long-term relationships and institutional partnerships. Conversely, Kresge's narrower scope of inquiry and negotiations created tensions among stakeholders, shunting many Kresge-backed plans outside formal planning processes. This research further reveals that foundations' limited democratic accountability and mismatched stakeholder expectations lead to democratic tensions. Foundations' constraints in resources, authority, and democratic representativeness, in turn, open opportunities for planners to improve both processes and outcomes of foundation-driven urban development.
The spatial relationship between morphological and functional centers influences the efficiency of resource allocation and the coordination of spatial structure. However, existing studies predominantly focus on macro-level trend analysis, lacking not only typological examinations based on their spatial relationships but also investigations into the factors influencing these spatial relationships. Using ASEAN as a case study, this paper identifies its morphological and functional centers, conducts a comparative analysis across different economic development stages, and examines their spatial relationships, typologies, and underlying drivers. The results reveal three key findings: (1) Morphological centers in ASEAN cities generally display polycentric and dispersed patterns, while functional centers tend to be monocentric and concentrated. (2) The spatial linkage between morphological and functional centers is heterogeneous and closely tied to economic development stages. Among these factors, Fragmentation, Transportation, and History remain consistently influential across all stages. In contrast, the influence of Foreign Direct Investment (FDI) and industrial parks exhibits a growing trend during the middle and later stages of economic development. (3) While the number, scale, and spatial relationships of morphological and functional centers vary distinctly across different economic development stages, their spatial distribution characteristics exhibit notable commonalities.
We develop an analytical framework of knowledge complementary potential of cities for firms and its innovation effects, and conduct empirical analysis based on 998 listed firms in China. We find that the complementary knowledge (CK) significantly increases the likelihood of technological diversification, and this effect does not exist in isolation but forms a complementary relationship with the firm's knowledge relatedness density. Heterogeneity analysis reveals that the innovation effects of CK vary substantially across different types of firms. In high-tech industries and private firms, the effect relies more heavily on the support of firms' internal knowledge structures; whereas in non-high-tech industries and state-owned firms, CK also exerts a direct promoting effect.
