Applied Spatial Analysis and Policy最新文献

Since Airbnb’s launch in 2008, the for‑profit housing‑sharing economy has been linked to overtourism and worsening housing affordability worldwide. Against this backdrop, the paper at hand examines spatial links between tourism accommodation and housing affordability in Greece’s two largest cities, Athens and Thessaloniki, using detailed neighborhood‑level data on Airbnb listings, conventional hotels, and average residential rents and sale prices. Specifically, the paper first maps the short‑term rental market and the residential rental market separately, then examines their interlinkages through spatial analysis, and finally employs spatial and non‑spatial regressions to disentangle these relationships. Its findings highlight that the spatial patterns of these two markets differ profoundly between the two cities under study, yet consistently show a positive association between high densities of short-term rentals and higher residential rents. Going beyond the level of granularity of most prior studies, the findings document how this relationship varies in nature and intensity across parts of each city, while also emphasizing the role of nightly Airbnb prices. Finally, the analysis confirms a strong link between residential rents and sale prices which—alongside expected building and neighbourhood effects and established price‑to‑rent ratios—brings attention to the growing influence of buy‑to‑rent investment and housing policies. Overall, the paper nuances common conclusions of the relevant literature around short‑term rentals and residential uses, contributes to the sparse literature on these dynamics in Greece, and enriches debates on speculative real estate investment.

Construction Land Reduction (CLR) has emerged as a pivotal policy in China for optimizing land-use spatial structure, particularly in metropolitan suburbs. This study develops a novel "simulated reverse extrapolation" framework to quantify its effects, integrating the PLUS model with FRAGSTATS to assess CLR intensity and landscape patterns in Shanghai's suburbs. Our findings demonstrate that CLR significantly enhances landscape connectivity and curbs urban sprawl, mechanisms primarily driven by edge and agglomeration effects. These impacts, however, are heterogeneous, varying substantially with local land supply types, industrial development levels, and geographical context. Spatial econometric analysis of 96 suburban townships (2014–2024) confirms a significant spatial interdependence between CLR and land-use structure. The Spatial Durbin Model further reveals a nuanced spillover effect: while CLR robustly improves landscape connectivity within implementing towns, it generates negative externalities by reducing connectivity in adjacent areas. These insights provide critical empirical evidence for refining ecological civilization initiatives and optimizing territorial spatial planning.

Soundscape research has made important progress in understanding both environmental determinants and personal factors. However, large-scale investigations of how these factors interact in real-world residential soundscapes remain limited. This study uses survey data from 1,918 adult residents in Guangzhou, China, employing generalized ordered logistic regression and mediation analysis to examine relationships between environmental and personal factors, sound type perception, and soundscape satisfaction in residential areas. Results support both hypotheses. Personal factors—daily activity radius and demographics—significantly shape soundscape outcomes beyond environmental factors alone (H1), with more mobile residents reporting higher anthropogenic sound perception and consequently lower satisfaction. Sound type perception mediates the relationship between personal factors and satisfaction (H2) through diverse pathways, for example: full mediation for mobility and education (operating entirely through acoustic perception), competitive partial mediation for gender (acoustic sensitivity counterbalanced by other factors), and threshold-specific patterns for household registration status (acoustic barriers intensifying at higher satisfaction levels). These findings highlight the importance of incorporating personal factors in soundscape research and urban planning.

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.