Applied Spatial Analysis and Policy最新文献

This study examines how neighbourhood built environments influence older adults’ nature connectedness and subjective wellbeing, with particular attention to green and blue spaces and their effects through greenspace visitation frequency and duration. Understanding these interrelations is essential for enhancing nature connections that support health and wellbeing across all ages. Using multilevel structural equation modelling and multilevel linear modelling, we analysed data from older adults in Guangzhou, China, examining both direct and indirect pathways linking built environment features to subjective wellbeing through nature connectedness and greenspace visitation patterns. Results showed that nature connectedness and greenspace visitation duration directly enhanced older adults’ subjective wellbeing, while greenspace visitation frequency influenced subjective wellbeing indirectly through strengthened nature connectedness. Regarding neighbourhood environment effects, population density and greenspace ratio were positively associated with subjective wellbeing, whereas building density, point-of-interest diversity, street greenery, and distance to water showed negative associations. Notably, distance to water was the only built environment attribute significantly affecting nature connectedness, with this relationship being substantially stronger among residents who had lived in Guangzhou for less than five years compared to long-term residents. This study reveals complex relationships between built environments, nature connectedness, and subjective wellbeing, highlighting the importance of both direct environmental effects and individual differences in sensitivity to environmental features. The research extends the existing nature connectedness-subjective wellbeing literature conceptually, and takes life course factors into the modelling process. These findings offer insights for urban planners to enhance nature connectedness and effectively improve older adults’ subjective wellbeing through targeted environmental interventions.

This study offers a descriptive spatial analysis of the potential demand and effective supply of care services for dependent older adults in Chile. By integrating sociodemographic data from administrative registries with the geographic distribution of public and private institutions providing care to older adults, across all 16 regions and 6,877 neighborhood units (unidades vecinales, UVs), the analysis identifies substantial territorial disparities in access to long term residential facilities (ELEAM) and community based programs (CEDIAM). In the Metropolitan Region, residents have access to an average of 11.6 ELEAMs within a 3 km radius. In contrast, in Aysén and Magallanes, the average distance to the nearest facility exceeds 400 km, with fewer than one center within a comparable range. Public provision, particularly through the National Service for Older Adults (SENAMA), demonstrates the lowest accessibility and further concentrates care infrastructure in urban areas. While for-profit providers exhibit greater spatial dispersion, their expansion is predominantly influenced by market forces, resulting in systematic underservice in low-income and remote areas. Spatial analysis substantiates this disparity: dependent older adults are highly concentrated in specific neighborhoods (Moran’s I = 0.92), whereas care facilities are primarily located in urban centers, proving territorial misalignment between demand and supply. These results highlight the importance of integrating spatial equity criteria into the development of Chile’s National Care System. Enhancing the nonprofit sector through regulatory frameworks and targeted subsidies could address territorial disparities caused by limited public coverage and market-driven provision, thereby fostering a more equitable and territorially balanced care model.

This paper applies a Potts model to segment the demand of local housing markets in New South Wales, Australia, using a Markov Chain Monte Carlo (MCMC) estimation approach. This approach models both endogenous spatial dependence and heterogeneity. The results identify 10 distinct market segments where housing demand responds similarly to income changes, revealing regional disparities through spatial patterns. Metropolitan Sydney and coastal regions exhibit the highest income elasticity (0.57-0.6), indicating strong demand, while inland areas show moderate responses (0.51-0.53), and remote regions the lowest, often below 0.5. These findings highlight spatial inequality in housing market performance, with implications for place-based policies such as affordable housing initiatives and regional investment to promote more equitable outcomes across NSW.

As the pursuit of quality life continues to increase and the environmental and health challenges become greater after COVID-19, a large number of older adult amenity migrants (OAM) are relocating to areas with superior environments. This study aims to investigate the relationship between greenspace characteristics and older adult amenity migrants’ subjective well-being (OAMSWB), which can deepen the environmental needs of the elderly in second-home and provide guidance for enhancing their well-being. Using Maodao Town in Lichuan City, an ecological tourism destination in China, as a case study, we integrate greenspace with social survey data to build multilevel ordered logistic models that examine how availability, accessibility, landscape patterns, tranquility, and attractiveness influence OAMSWB. Mediating variables (e.g., frequency of visits and exercise) were integrated into the analysis, to create a multilevel mediator model. The results show that, (1) Greenspace characteristics have positively affected on the OAMSWB, though the strength of each dimension varies. (2) Frequency of visits has a significant mediating effect, tranquility, and attractiveness can enhance the OAMSWB by increasing the frequency of visits, but availability, accessibility and landscape patterns, although increasing the frequency of visits, can cause overcrowding and other problems, which leads to the decline of the OAMSWB. (3) Different dimensions of greenspace features interact complementarily, jointly amplifying their impact on OAMSWB. This study reveals the complex links between greenspace characteristics and OAMSWB, and provides targeted policy recommendations for second-home planners to optimize the layout, improve the quality of greenspace, and propose targeted policies.

Major pandemic outbreaks have profound global social and economic consequences, underscoring the urgency for cities to adopt adaptive preparedness strategies. During such outbreaks, municipal governments often implement broad containment measures, including mobility restrictions. While these measures are crucial for protecting public health, their application without a nuanced understanding of local pandemic conditions can disrupt socioeconomic systems and disproportionately burden communities. Effective strategies must therefore integrate localized assessments of pandemic vulnerability and precise, neighborhood-level responses to mitigate adverse social and economic impacts. Using data from the COVID-19 pandemic outbreak, this research develops a dual-focused framework to evaluate urban pandemic vulnerability through the intersecting lenses of infection risk and vaccination accessibility. The proposed framework integrates the Spatially-Tuned Poisson Regression machine learning technique to empirically calibrate the distance-decay parameter, allowing the vaccination accessibility model to better reflect the average pull of vaccination sites.​​ Applied to the high-density urban context of Hong Kong, the analysis identifies localized vulnerability patterns at the smallest census unit level, revealing heightened pandemic vulnerabilities in areas of Kowloon, northern Hong Kong Island, and select new towns in the New Territories. These findings demonstrate how spatially explicit assessments prioritize neighborhoods for targeted risk identification and mitigation strategies, offering a transferable framework for precise outbreak response during future pandemic outbreaks.

While highly educated talents are crucial for urban innovation and regional sustainable development, limited research has examined how environmental amenities affect their destination preference, particularly considering spatial heterogeneity and scale effects. Drawing on China’s 2020 Seventh National Population Census data across 337 cities, this study employs Multiscale Geographically Weighted Regression (MGWR) model to investigate the spatial patterns and determinants of highly educated talents in China, with a specific focus on environmental amenities. The results show that highly educated talents are primarily concentrated in provincial capitals, municipalities directly under the central government, separately administered cities, and resource-based cities in northern China. In contrast, southeastern China offers more favorable environmental amenities compared to the northwest, highlighting significant spatial disparities. Furthermore, the MGWR model outperforms the OLS and GWR models, with the Temperature-Humidity Index (THI) demonstrating a broader influence than PM_2.5 and the Normalized Difference Vegetation Index (NDVI). In addition, environmental amenities exhibit multilevel spatial heterogeneous effects on destination preferences of highly educated talents in China. Specifically, THI has a stronger positive effect in certain central and western cities. Our findings offer valuable insights for enhancing regional competitiveness through environmental quality improvements.

This paper evaluates the impact of urban flood risk on housing prices using historical heavy rainfall and flood simulation data. The authors analyzed a dataset of 2055 second-hand residential prices, finding that flooding does not significantly disrupt the housing market in Nanjing. Quantile regressions indicate that a 1 km flood inundation area notably affects high-priced neighborhoods, while proximity to waterlogged areas has a greater impact on low-priced neighborhoods. Geographically weighted regressions show spatial variability in how flooding influences housing prices. Sensitivity to flooding is primarily concentrated in areas characterized by low-lying terrain, aging neighborhoods, topographical constraints, underdeveloped infrastructure, or lower-intensity urban development. Factors such as building characteristics, location attributes, and neighborhood features significantly influence the relationship between flooding and housing prices.

Digital economy policies, acting as a sturdy cornerstone for the development of the digital economy, play a pivotal role in stimulating entrepreneurial vitality of the logistics industry. This study leverages panel data from 277 cities in China spanning the period from 2009 to 2022 to conduct an in-depth exploration of the impact of digital economy policies on entrepreneurial vitality of the logistics industry, their underlying operational mechanisms, and their heterogeneous effects across different cities. The empirical findings indicate that digital economy policies DEPs exert a positive and lagged impact on the entrepreneurial vitality of the logistics industry. The results of the mechanism tests reveal that digital economy policies can elevate entrepreneurial vitality of the logistics industry through three crucial channels: promoting the construction of digital infrastructure, fostering digital innovation vitality, and providing talent support. The heterogeneity analysis uncovers that digital economy policies exhibit more pronounced positive effects in advanced cities and e-commerce demonstration cities. This study not only deepens our understanding of the relationship between digital economy policies and entrepreneurial vitality of the logistics industry but also provides a scientific basis for policymakers to implement targeted and precise policies, while simultaneously facilitating the high-quality development of logistics enterprises.

The construction of the Three Gorges Project has triggered profound transformations in the Rural Production Space System (RPSS) of the Three Gorges Reservoir Area (TGRA), characterized by land submergence, population resettlement, and industrial restructuring. While existing studies have explored these changes from sectoral perspectives, the application of life cycle theory to analyze RPSS evolution remains a critical gap. This study develops a novel analytical framework integrating life cycle theory to systematically examine the spatiotemporal dynamics of RPSS transformation in the TGRA from 1990 to 2020. We identify three core subsystems population, land, and industry and reveal their distinct transition trajectories: population and land transformations peaked before 2010, driven by urbanization and resettlement policies, while industrial transformation surged post-2010 under endogenous growth mechanisms. Notably, the RPSS transitioned from a “blood transfusion” model (external resource dependency) to a “blood production” model (self-sustaining development), highlighting the interplay of policy interventions and internal adaptations. Theoretically, this study pioneers the integration of life cycle theory into rural spatial system analysis, offering methodological advancements for complex system transitions. Finally, we propose actionable strategies “green industrial transformation, urban-rural integration, and institutional reforms” to address sustainability challenges in the TGRA, with implications for global regions impacted by large-scale hydraulic projects.

Reducing spatial inequality has been a central objective of Morocco’s Advanced Regionalization Project since 2015, yet regional disparities persist and continue to deepen. The twelve Moroccan regions evolve at different speeds, reflecting the enduring effects of core–periphery structures, path dependence, and spatial lock-ins that channel resources toward coastal growth poles while constraining peripheral territories. This research investigates the mechanisms behind these unequal trajectories, focusing on how demand-side welfare gaps, investment efficiency, and localized institutional capacity shape spatial inequality across regional, provincial, and municipal levels. Using spatial econometric estimation combined with nighttime-light data as a proxy for economic activity, the study reveals that while urban consumption and population concentration drive growth in illuminated cores, investments fail to generate inclusive spillovers. These structural imbalances reinforce geographic polarization and undermine the goals of territorial cohesion and social equity. Results reveal that growth and light intensity are concentrated in illuminated cores where consumption and population density reinforce cumulative advantages, whereas investment shows weak spillover capacity and often amplifies the core–periphery divide. These findings demonstrate that inequality in Morocco is not solely an income outcome but a manifestation of spatially embedded development structures and governance asymmetries. The evidence calls for a reorientation from uniform, top-down policies toward place-based strategies that leverage local potential, strengthen institutional capacity, and promote inclusive investment. Beyond Morocco, the analysis offers insights for developing countries facing similar spatial divides, highlighting the need for territorially sensitive approaches to achieve the SDGs on decent work, reduced inequalities, and sustainable cities.