Search Results (207)

Context: It has been claimed that recently, in England, the places with the greatest amount of housing built were the places that least needed them. This is an accusation that has echoes in a number of countries around the globe. The lack of construction leads to greater unaffordability and a lower level of economic activity than could have been achieved if labour, particularly those with high human capital, was not so constrained as to where they could afford to live. The recent National Planning Policy Framework for England imposes mandatory targets on housing planning authorities. As such, the following question is raised: will the targets result in additional residential homes being located in places of greater need than the prevailing pattern? Research Questions: The paper sets out to consider the spatial mismatch between housing additions and national benefit in terms of unaffordability and productivity. Specifically, do the concentrations of high and/or low rates of the prevailing rates of additional dwellings and the target rates of adding dwellings correspond with the clusters of high and/or low unaffordability and productivity? A further question considered is: does the spatial distribution of additional dwellings match the clusters of population growth? Method: The values of the variables are transformed at the first stage into Anselin’s LISA categories. LISA maps can reveal unusually high spatial concentrations of values, or clusters. The second stage entails comparing sets of the transformed data for agreement of the classifications. An agreement coefficient is provided by Fleiss’s kappa. Data: The data used is of additional dwellings, the total number of dwellings, population estimates, gross value added per hour worked (productivity data), and house price–earnings ratios. The period of study covers the eight years prior to 2020 and the two years after, omitting 2020 itself due to the unusual impact on economic activity. All the data is at local authority district level. Findings: The hot and cold spots of additional dwellings do not correspond those of house price–earnings ratios or productivity. However, population growth hot spots show moderate agreement with those of where additional dwellings are concentrated. This is in line with findings from elsewhere, suggesting that population follows housing supply. Concentrations of districts with relatively high targets per unit of existing stocks are found correspond (agree strongly) with clusters of house price–earnings ratios. Links between productivity and housing are much weaker. Conclusions: The strong link between targets and affordability suggests that if the targets are met, the claim that the places that build the most housing are the places that least need them can be challenged. That said, house-price–earnings ratios present a view of unaffordability that will favour greater building in the countryside rather than cities outside of London, which runs against concentrating new housing in urban areas consistent with fostering clusters/agglomerations implicit in the new modern industrial strategy. Full article

As China’s urbanization deepens, the spatial structure of residential areas and land use patterns has undergone profound transformations, with the differentiation of housing prices emerging as a key indicator of urban spatial dynamics and socioeconomic stratification. This study examines the spatial and temporal evolution of residential housing prices in Qingdao’s main urban area over a 20-year period, using data from three representative years (2003, 2013, and 2023) to capture key stages of change. It employs Local Indicators of Spatial Association (LISA) spatial and temporal path and leap analyses, as well as Geographically and Temporally Weighted Regression (GTWR) modeling. The results show that Qingdao’s housing price patterns exhibit distinct spatiotemporal heterogeneity, characterized by multi-level transitions, leapfrog dynamics and strong spatial dependence. The urban center and coastal zones demonstrate positive synergistic growth, while some inland and peripheral areas show negative spatial coupling. Evident is the spatial restructuring from a monocentric to a polycentric pattern, driven by shifts in industrial layout, policy incentives, and transportation infrastructure. Key driving factors, such as community attributes, locational conditions, and amenity support, show differentiated impacts across regions and over time. Business agglomeration and educational resources are primary positive drivers in central districts, whereas natural environments and commercial density play a more complex role in peripheral areas. These findings provide empirical evidence to inform our understanding of housing market dynamics and offer insights into urban planning and the design of equitable policies in transitional urban systems. Full article

To solve the present housing crisis, the Support for Access to Housing Program, in the context of PRR, mainly focuses on social housing to be built or on housing of social interest to be regenerated. To approach this problem, a research question was raised: “What is the significance of the existing cooperative housing in solving the current housing crisis?” To analyze this issue, a multiple case study was adopted, comparing a collective dwelling of cooperative promotion at controlled costs in Caselas (1980s–1990s) with Expo Urbe (2000–2007) in Parque das Nações, a symbol of the new sustainable cooperative housing, which targets a population with a higher standard of living and thus is excluded from the PRR plan. These cases revealed the discrepancy created by the Cooperative Code of 1998 and its consequences for the urban regeneration of this heritage. They show that Caselas, built in a residential urban neighborhood, is strongly attached to a community, provides good social inclusion for vulnerable groups at more affordable prices, and it is eligible for urban regeneration and reuse (for renting or buying). However, the reuse of Caselcoop’s edifices cannot compromise their cultural and residential values or threaten the individual integrity. Full article

Numerous studies have demonstrated that in residential areas of Western cities, both luxury and legacy effects significantly shape tree species diversity dynamics. However, the specific mechanisms driving these diversity patterns in China, where urbanization has progressed at an unprecedented pace, remain poorly understood. In this study we selected 20 residential settlements and 7 key socio-economic properties to investigate the change trend of tree diversity (2006–2021) and its socio-economic driving factors in Beijing. Our results demonstrate significant increases in total, native, and exotic tree species richness between 2006 and 2021 (p < 0.05), with average increases of 36%, 26%, and 55%, respectively. Total and exotic tree Shannon-Wiener indices, as well as exotic tree Simpson’s index, were also significantly higher in 2021 (p < 0.05). Housing prices was the dominant driver shaping total and exotic tree diversity, showing significant positive correlations with both metrics. In contrast, native tree diversity exhibited a strong positive association with neighborhood age. Our findings highlight two dominant mechanisms: legacy effect, where older neighborhoods preserve native diversity through historical planting practices, and luxury effect, where affluent communities drive exotic species proliferation through ornamental landscaping initiatives. These findings elucidate the dual dynamics of legacy conservation and luxury-driven cultivation in urban forest development, revealing how historical contingencies and contemporary socioeconomic forces jointly shape tree diversity patterns in urban ecosystems. Full article

China’s rapid urbanization has driven tremendous socioeconomic development while posing new forms of social–spatial inequalities that challenge environmental sustainability and spatial justice. This study investigates urban park-accessibility patterns across 10 s-tier provincial capital cities in China, examining how these patterns relate to housing-price dynamics to reveal diverse manifestations of social–spatial (in)justice. Using comprehensive spatial analysis grounded in distributive justice principles, we measure park accessibility through multiple metrics: distance to the nearest park, park size, and the number of parks within a 15 min walk from residential communities. Our findings reveal significant variation in park accessibility across these cities, with distinctive patterns emerging in the relationship between housing prices and park access that reflect different forms of social–spatial exclusion and inclusion. While most cities demonstrate an unbalanced spatial distribution of parks, they exhibit different forms of this disparity. Some cities show consistent park access across housing-price categories, while others display correlations between high housing prices and superior park accessibility. We argue that these divergent patterns reflect each city’s unique combination of economic development trajectory, politically strategic positioning within national urban hierarchies, and geographical constraints. Through this comparative analysis of second-tier cities, this study contributes to broader understandings of social–spatial (in)justice and urban environmental inequalities within China’s urbanization process, highlighting the need for place-specific approaches to achieving equitable access to urban amenities. Full article

This study empirically delves into whether residential heating methods significantly affect apartment prices in Uiwang City, a suburban city near the Seoul Metropolitan area, South Korea. Using data from 1256 apartment sales, where both district heating systems (DHSs) and individual heating systems (IHSs) coexist, a hedonic price equation was estimated to analyze the impact of the heating method choices on housing values. Various housing attributes, including physical, locational, and environmental factors, were controlled, and multiple regression models were compared to identify the best-performing specification. The results show that apartments equipped with a DHS are priced, on average, KRW 92 million (USD 72 thousand) higher than those with an IHS. The price difference corresponds to KRW 849 thousand (USD 665) per m² and possesses the statistical significance at the 5% level. Moreover, it is quite meaningful, representing roughly 11.2% of the price of an average apartment. These findings suggest that the use of DHS has a positive effect on apartment prices that reflect consumers’ preferences, beyond its advantages in stable heat supply and energy cost savings. This article provides empirical evidence that DHS can serve as an important urban infrastructure contributing to asset value enhancement. Although this study is based on a specific geographic area and caution must be exercised in generalizing its findings, it reports the interesting finding that residential heating method significantly affects housing prices. Full article

With the rapid advancement of urbanization, the increasing demand and insufficient supply of public service facilities for children have become urgent problems requiring resolution. This study employs the Shannon diversity index, the location entropy, spatial autocorrelation, and the Geographically Weighted Regression (GWR) to analyze the spatial distribution characteristics and influencing factors of children’s public service facilities in the central urban area of Shenyang. The findings of the study are as follows: (1) There are significant differences in the spatial distribution of children’s public service facilities. Higher quantity distribution and diversity index are observed in the core area and Hunnan District compared to the peripheral areas. The Gini coefficient of various facilities is below the fair threshold of 0.4, but 90.32% of the study units have location entropy values below 1, indicating a supply–demand imbalance. (2) The spatial distribution of various facilities exhibits significant clustering characteristics, with distinct differences between high-value and low-value cluster patterns. (3) The spatial distribution of facilities is shaped by four factors: population, transportation, economy, and environmental quality. Residential area density and commercial service facility density emerge as the primary positive drivers, whereas road density and average housing price act as the main negative inhibitors. (4) The mechanisms of influencing factors exhibit spatial heterogeneity. Positive driving factors exert significant effects on new urban areas and peripheral zones, while negative factors demonstrate pronounced inhibitory effects on old urban areas. Non-linear threshold effects are observed in factors such as subway station density and public transport station density. Full article

This study examines the demographic and macroeconomic factors influencing housing prices in London from Q3 2014 to Q4 2022, focusing on the pre- and post-Brexit referendum periods. Using multiple regression analysis, the research evaluates the impact of interest rates, inflation, construction costs, population changes, and net migration on the housing price index (HPI) across various market segments. The findings suggest that interest rate base rates, consumer price inflation, and construction output price indices were significant predictors of housing price fluctuations. Notably, cash purchases exhibited the strongest explanatory power due to a reduced sensitivity to market changes. Additionally, London’s population was a key determinant, particularly affecting first-time buyers and mortgage-backed purchases. These results contribute to a deeper understanding of the London housing market and offer insights into policy measures addressing housing affordability and investment dynamics. Full article

Jobs–housing balance is a critical concern in urban planning and sustainable economic development. Urban rail transit, as a key determinant of employment and residential location decisions, plays a pivotal role in shaping jobs–housing dynamics. Beijing, the first Chinese city to develop a subway system, offers a comprehensive rail network, making it an ideal case for exploring the effects of transit density on jobs–housing balance. This study utilizes medium-scale panel data from Beijing (2009–2022) and employs a fixed-effects model to systematically examine the impact of rail transit station density on jobs–housing balance and its underlying mechanisms. The results indicate that increasing transit station density tends to aggravate jobs–housing separation overall, with pronounced effects in central and outer suburban areas but negligible effects in near suburban areas. Mechanism analysis reveals two primary pathways: (1) improved accessibility draws employment toward transit-rich areas, reinforcing the attractiveness of central districts; (2) rising housing prices elevate residential thresholds, pushing lower-income populations toward outer suburbs. While enhanced transit density improves commuting convenience, it does not effectively reduce jobs–housing separation. These findings offer important policy implications for optimizing transit planning, improving jobs–housing alignment, and promoting sustainable urban development. Full article

Urban green spaces (UGSs), including parks, forests, and community gardens, play a critical role in enhancing public health and well-being by providing essential ecosystem services such as improving air quality, reducing surface temperatures, and mitigating harmful substances. As urbanization accelerates, especially in rapidly growing cities like Jinan, China, the demand for UGSs is intensifying, necessitating careful urban planning to balance development and environmental protection. While previous studies have often focused on city-level green coverage, this study shifts the analytical focus from UGS as a whole to urban functional units (UFUs), allowing for a more detailed examination of how green space is distributed across different land use types. We investigate UGS changes in Jinan over the past two decades and assess the influence of socio-economic factors—such as housing prices, land use types, and building age—on UGS distribution within UFUs. Remote sensing technology was employed to analyze the spatiotemporal dynamics of UGS and its correlation with these variables. Our findings reveal a significant shift in UGS distribution, with parks and leisure areas becoming primary drivers of UGS expansion. This study also highlights the growing influence of economic factors, particularly housing prices, on UGS distribution in more affluent UFUs. Additionally, while UGS in Jinan has generally expanded, challenges remain in balancing green space with urban expansion, especially in commercial and residential UFUs. This paper contributes to a more nuanced understanding of UGS distribution by integrating the UFU framework and identifying socio-economic drivers—including housing prices, construction age, and land use type—that shape green space patterns in Jinan. Our findings demonstrate that the spatial pattern of UGS in Jinan mirrors socio-economic and land use disparities observed in other global cities, highlighting both the universality of these patterns and the need for targeted planning in rapidly urbanizing contexts. Full article

Urban regeneration is pivotal to sustainable development, requiring innovative strategies that align social dynamics with spatial configurations. Traditional paradigms increasingly fail to tackle systemic challenges—neighborhood alienation, social fragmentation, and resource inequality—due to their inability to integrate human-centered spatial governance. This study addresses these shortcomings with a novel multidimensional framework that merges social perception (life satisfaction) analytics with spatial quality (GIS-based) assessment. At its core, we utilize geospatial and machine learning models, deploying an ensemble of Gradient Boosted Decision Trees (GBDT), Random Forest (RF), and multiscale geographically weighted regression (MGWR) to decode nonlinear socio-spatial interactions within Suzhou’s community environmental matrix. Our findings reveal critical intersections where residential density thresholds interact with commercial accessibility patterns and transport network configurations. Notably, we highlight the scale-dependent influence of educational proximity and healthcare distribution on community satisfaction, challenging conventional planning doctrines that rely on static buffer-zone models. Through rigorous spatial econometric modeling, this research uncovers three transformative insights: (1) Urban environment exerts a dominant influence on life satisfaction, accounting for 52.61% of the variance. Air quality emerges as a critical determinant, while factors such as proximity to educational institutions, healthcare facilities, and public landmarks exhibit nonlinear effects across spatial scales. (2) Housing price growth in Suzhou displays significant spatial clustering, with a Moran’s I of 0.130. Green space coverage positively correlates with price appreciation (β = 21.6919 ***), whereas floor area ratio exerts a negative impact (β = −4.1197 ***), highlighting the trade-offs between density and property value. (3) The MGWR model outperforms OLS in explaining housing price dynamics, achieving an R² of 0.5564 and an AICc of 11,601.1674. This suggests that MGWR captures 55.64% of pre- and post-pandemic price variations while better reflecting spatial heterogeneity. By merging community-expressed sentiment mapping with morphometric urban analysis, this interdisciplinary research pioneers a protocol for socio-spatial integrated urban transitions—one where algorithmic urbanism meets human-scale needs, not technological determinism. These findings recalibrate urban regeneration paradigms, demonstrating that data-driven socio-spatial integration is not a theoretical aspiration but an achievable governance reality. Full article

Residential mobility within cities reflects the spatio-temporal patterns of individual or household relocation behaviors and serves as an effective tool for interpreting urban socio-spatial differentiation from a micro-level perspective. Newly employed college graduates (NECGs) have become the second-largest migrating population in China. This study selects Guangzhou, a megacity, as the study area and utilizes data from the “Guangzhou New Citizens’ Residential Mobility Survey” conducted in 2023. It applies spatio-temporal systems and the spatio-temporal path method based on time geography to explore the residential mobility trajectories of NECGs in Guangzhou. In addition, the study uses a logistic regression model to explore the influencing factors. The findings indicate that NECGs frequently move across districts, showing no significant patterns of concentration or dispersion. However, residential location choices vary considerably across educational levels and household registration natures (Hukou), and as the duration of residence in Guangzhou increases, the probability of residential mobility among NECGs across all educational levels shows a declining trend. Specifically, marital status (life course attributes), housing prices and medical facilities (housing attributes), and job type (socioeconomic attributes) emerge as critical factors influencing residential mobility. By providing a foundation for urban planning policies, this study aims to support the settlement and well-being of NECGs while promoting high-quality urban development in Guangzhou. Full article

The residential construction sector is critical to economic stability and housing availability. Residential construction demands often fluctuate due to demographic, economic, social, or market condition variables. This study seeks to investigate the significance of these external variables and produce a predictive model for residential construction demand using ElasticNet regression. Adopting New Zealand as a case study and leveraging datasets from Statistics New Zealand, this research identifies key demographic, economic, and market factors influencing four building categories: retirement villages, apartments, multiunit developments, and standalone houses. The research results indicate that age groups, particularly the 20−39 and 65+ age groups, and economic indicators, such as the house price index and unemployment rates, have high prediction powers. The models showed high accuracy for some categories, with R² values exceeding 0.87 for retirement villages and 0.91 for multi-units. Challenges were encountered with standalone houses and apartments due to residual variance. The research findings highlight the importance of targeted urban planning and policy adjustments to satisfy the requirements of specific age groups, address housing affordability and demographic shifts, and cater to prevailing market conditions. This research provides practical insights and guidance for urban planners, public housing agencies, residential developers, and residential contractors while offering a robust methodological framework for predictive modelling in the construction sector. Full article

Using ArcGIS software to conduct spatial autocorrelation analysis, it was found that the price distribution of rural homestays in Suzhou is not random but shows apparent spatial clustering. Among the 81 rural homestays were 9 high-high clusters, 25 low-low clusters, 1 high-low outlier, and 5 low-high outliers. The hedonic price model is an economic model that breaks down goods or services into multiple attributes to estimate their prices. Based on this model, this paper further investigates the differentiated impacts and interactions between internal accommodation characteristics and external environmental attributes in the pricing mechanism of rural homestays in Suzhou. The results show that (1) the high-priced rural homestays in Suzhou are concentrated in the lake island resort with good natural environment and perfect infrastructure; (2) the location, facility quality, and network score of rural homestays have a positive impact on housing prices; (3) the parking lot of rural homestays hurts housing prices; (4) the quality of rural residential buildings and facilities has the most significant positive impact on housing prices. By comparing the hedonic price model of rural homestay and the heterogeneous preferences of consumers, this study provides rural homestay operators with effective room pricing strategies and marketing implications, provides policymakers with reference factors to promote the development of rural homestay industry, and has specific guiding significance for the sustainable development of the homestay industry. Full article

Urban sprawl and excessive reliance on motorization have led to many urban problems. The balance of supply and demand in the real estate market, as well as price fluctuations, also face many challenges. Urban rail transit not only alleviates traffic congestion and air pollution, but also significantly reduces residents’ commuting time, broadens urban accessibility, and reshapes the decision-making basis for residents when choosing residential locations. This study takes the 1st, 2nd, 3rd, 4th, 8th, 11th, and 13th metro lines that have been opened in Qingdao City as examples. It selects 12,924 residential samples within a 2 km radius along the rail transit lines. By using GIS spatial analysis tools and the multi-scale geographically weighted regression (MGWR) model, it analyzes the spatial differentiation characteristics of housing prices along the rail transit lines and the reasons and mechanisms behind them. The empirical results show that housing prices decrease to varying degrees with the increase in the distance from the rail transit. For every additional 1 km from the rail transit station, the housing price increases by 0.246%. Through model comparison, it was found that MGWR has a better fitting degree than the traditional ordinary least squares method (OLS) and the previous geographically weighted regression model (GWR), and reveals the spatial heterogeneity of the influence of urban rail transit on housing prices. Different indicator elements have different effects on housing prices along these lines. The urban rail transit factor in the location characteristics has a positive impact on housing prices, and has a significant negative correlation in some areas. The significant influence range of the distance to the nearest metro station on housing prices is concentrated within a radius of 373 m, and the effect decays beyond this range. The total floors, building area, green coverage rate, property management fee, and the distance to hospitals and parks in the neighborhood and structural characteristics have spatial heterogeneity. Analyzing the areas affected by the urban rail transit factor, it was found that the double location superposition effect, the networked transportation system, and the agglomeration of urban functional axes are important reasons for the significant phenomena in some local areas. This research provides a scientific basis for optimizing the sustainable development of rail transit in Qingdao and formulating differentiated housing policies. Meanwhile, it expands the application of the MGWR model in sustainable urban spatial governance and has practical significance for other cities to achieve sustainable urban development. Full article