Search Results (52)

Japan’s 8.5 million vacant homes (Akiyas) represent a paradox of scarcity amid surplus: while rural depopulation leaves properties abandoned, housing shortages and bureaucratic inefficiencies hinder their reuse. This study proposes AKI2ALL, an AI-blockchain framework designed to automate the circular repurposing of Akiyas into ten high-value community assets—guesthouses, co-working spaces, pop-up retail and logistics hubs, urban farming hubs, disaster relief housing, parking lots, elderly daycare centers, exhibition spaces, places for food and beverages, and company offices—through smart contracts and data-driven workflows. By integrating circular economy principles with decentralized technology, AKI2ALL streamlines property transitions, tax validation, and administrative processes, reducing operational costs while preserving embodied carbon in existing structures. Municipalities list properties, owners select uses, and AI optimizes assignments based on real-time demand. This work bridges gaps in digital construction governance, proving that automating trust and accountability can transform systemic inefficiencies into opportunities for community-led, low-carbon regeneration, highlighting its potential as a scalable model for global vacant property reuse. Full article

Urbanization is one of the most important challenges contributing to the trend of replacing agricultural land with high-value land uses, such as housing, as well as industrial and commercial activities, as a result of significant population growth. To face these challenges and improve urban sustainability, integrating an embedded concept of spatial planning, taking into account urban and peri-urban agriculture, will contribute to mitigating food security issues and the negative impact of climate change, while improving social and economic development. This project aims to analyze land use/cover changes in the Casablanca metropolitan area and its surrounding cities, which are undergoing rapid urban growth. To achieve this, time series of remote sensing data were analyzed in order to investigate the spatio-temporal changes in LU/LC and to evaluate the dynamics and spatial pattern of the city’s expansion over the past three decades, which has come at the expense of agricultural land. The study will also examine the relationship between urbanization and agricultural land use change over time. The results of this study show that Casablanca and its outskirts experience significant urban expansion and a decline in arable lands, with rates of 45% and 42%, respectively. The analysis of SDG indicator 11.3.1 has also shown that land consumption in the provinces of Mediouna, Mohammadia, and Nouaceur has exceeded population growth, due to rapid, uncontrolled urbanization at the expense of agricultural land, which highlights the need to develop a new conceptual framework for regenerating land systems based on the implementation of urban and peri-urban agriculture in vacant sites within urban and peri-urban areas. This will offer valuable insights for policymakers to investigate measures that can ensure sustainable land use planning strategies that effectively integrate agriculture into urban development. Full article

The flood risk of urban buildings has been continuously increasing, owing to the increasing frequency and severity of floods. There is an urgent need to implement precise mitigation strategies to address the unique characteristics of urban residential structures. In this study, an indicator system consisting of 17 indicators in four dimensions (extent of hazard, degree of exposure, vulnerability, and response ability) was developed for the flood risk of residential buildings. The assessment was conducted in Katsushika Ward, Tokyo, and the ANALYTIC HIERARCHY PROCESS(AHP)—Criteria Importance Through Intercriteria Correlation (CRITIC) method was integrated with Geographic Information System(GIS) technology. The spatial distribution of residential flood risk exhibits marked heterogeneity, with ‘extremely high’ and ‘high’ risk areas concentrated in northwestern and southwestern riverine zones. These regions exhibit dense populations, substantial assets, deep immersion depths, prolonged inundation durations, high proportions of wooden houses, and narrow roads impeding rescue operations. The mitigation priorities are the following: Enhance flood-resistant building heights and quality in riverside areas, strengthen vacant house management, widen rescue access routes, promote mid-/high-rise buildings, and optimize subsidies for tenants and single-person households to minimize losses. Full article

In Japan, vacant houses are widely recognized as a significant societal challenge. At the same time, the problems associated with vacant lots and land with unknown ownership are escalating and are expected to worsen in the future. In response, community organizations such as NPOs (nonprofit organizations), neighborhood associations, and government agencies have been central in increasing efforts toward effectively utilizing and managing these vacant properties. This study analyzed six cases supported by the MLIT (Ministry of Land, Infrastructure, Transport and Tourism) under the Land Bank initiative, with two cases involving land readjustment and four involving temporary use. A detailed examination of these pilot efforts and their application methods clearly highlights the necessity of integrating land management with urban planning. Furthermore, it has been found that there are several challenges in the Land Bank initiative, including difficulties in assessing market value, ownership issues, and the need for broad coordination. These findings provide important implications for improving Japan’s management of vacant land and houses. Full article

In view of the challenges brought by a complex environment, diverse data sources and urban development needs, our study comprehensively reviews the application of algorithms in urban residential vacancy rate observation. First, we explore the definition and measurement of urban residential vacancy rate, pointing out the difficulties in accurately defining vacant houses and obtaining reliable data. Then, we introduce various algorithms such as traditional statistical learning, machine learning, deep learning and ensemble learning, and analyze their applications in vacancy rate observation. The traditional statistical learning algorithm builds a prediction model based on historical data mining and analysis, which has certain advantages in dealing with linear problems and regular data. However, facing the high nonlinear relationships and complexity of the data in the urban residential vacancy rate observation, its prediction accuracy is difficult to meet the actual needs. With their powerful nonlinear modeling ability, machine learning algorithms have significant advantages in capturing the nonlinear relationships of data. However, they require high data quality and are prone to overfitting phenomenon. Deep learning algorithms can automatically learn feature representation, perform well in processing large amounts of high-dimensional and complex data, and can effectively deal with the challenges brought by various data sources, but the training process is complex and the computational cost is high. The ensemble learning algorithm combines multiple prediction models to improve the prediction accuracy and stability. By comparing these algorithms, we can clarify the advantages and adaptability of different algorithms in different scenarios. Facing the complex environment, the data in the observation of urban residential vacancy rate are affected by many factors. The unbalanced urban development leads to significant differences in residential vacancy rates in different areas. Spatiotemporal heterogeneity means that vacancy rates vary in different geographical locations and over time. The complexity of data affected by various factors means that the vacancy rate is jointly affected by macroeconomic factors, policy regulatory factors, market supply and demand factors and individual resident factors. These factors are intertwined, increasing the complexity of data and the difficulty of analysis. In view of the diversity of data sources, we discuss multi-source data fusion technology, which aims to integrate different data sources to improve the accuracy of vacancy rate observation. The diversity of data sources, including geographic information system (GIS) (Geographic Information System) data, remote sensing images, statistics data, social media data and urban grid management data, requires integration in format, scale, precision and spatiotemporal resolution through data preprocessing, standardization and normalization. The multi-source data fusion algorithm should not only have the ability of intelligent feature extraction and related analysis, but also deal with the uncertainty and redundancy of data to adapt to the dynamic needs of urban development. We also elaborate on the optimization methods of algorithms for different data sources. Through this study, we find that algorithms play a vital role in improving the accuracy of vacancy rate observation and enhancing the understanding of urban housing conditions. Algorithms can handle complex spatial data, integrate diverse data sources, and explore the social and economic factors behind vacancy rates. In the future, we will continue to deepen the application of algorithms in data processing, model building and decision support, and strive to provide smarter and more accurate solutions for urban housing management and sustainable development. Full article

Urban greenspaces, such as parks and other public vegetated spaces, provide respite from the built environment for residents and visitors. Lesser-known urban greenspaces are community-managed open spaces (CMOSs), such as play lots, community gardens, and memorial gardens. This study investigated the effect of the distance to and size of parks and CMOSs on residential house prices in Baltimore, MD, in 2016–2017 using a hedonic price model. This is the first study of an urban city comparing parks and CMOSs. The study included 21,116 houses sold and revealed that park proximate price premiums ranged from 7.73% to 11.01% for distances of up to a 1/2 mile, and the CMOS proximate price premiums were 8.69% and 8.96% for distances of up to 1/8 and 1/4 miles, respectively. Moreover, both parks and CMOSs revealed a buyer preference of a 1/8 to 1/2 mile distance from these urban greenspaces. Small- to medium-sized parks, less than 9.65 acres, increased house prices by approximately 2.36%, and small CMOSs, less than 0.24 acres, increased house prices by 5.93%. These results confirm that parks and CMOSs provide economic benefits in addition to their social, health, and well-being benefits and suggest that CMOSs are a viable economic development strategy for communities. Full article

Adaptive reuse of vacant houses in Japan offers an innovative and sustainable solution to the increase in vacant houses. This approach aligns with principles of sustainable architecture and the circular economy by reducing waste, lowering energy consumption, and extending the lifecycle of existing structures. This study uses purposive sampling, analyzing 262 adaptive reuse cases across Japanese prefectures through partial surveys, municipal records, and online maps. K-prototype clustering identified three distinct patterns. Cluster 1 emphasizes modern businesses, such as food, beverage, and accommodation services, within urban areas to address the needs of densely populated regions and tourist hubs. Cluster 2 blends urban and rural contexts, balancing historical preservation with modern functionality. Cluster 3 highlights rural and scenic accommodations that cater to tourists seeking cultural immersion and authentic experiences, despite challenges like low population density and limited accessibility. These findings contribute to the theoretical understanding of adaptive reuse as a key strategy for repurposing underutilized spaces, promoting both economic and social resilience. In practical terms, it demonstrates how adaptive reuse advances circular economy objectives by preserving cultural heritage, enhancing environmental sustainability, and creating economic opportunities. Further investigation is needed to unlock the unexplored potential of adaptive reuse in broader contexts and functions. Full article

The trend of gated communities is becoming the new alternative housing for the high-end residents of Jordan, reflecting global patterns of urbanisation. However, their emergence on the outskirts of Amman on vacant lands requires an early proactive planning approach to ensure their development in response to the growth of the surrounding areas, fostering an integrated urban fabric. This article examines whether gated communities contribute to urban discontinuity and lead to social segregation. The study employs a space syntax analysis on two cases in Amman to assess their integration, accessibility, and navigability to address the study’s key questions related to its integration, design implications, and spatial layout. Findings reveal significant spatial segregation, with low levels of integration and high step depth values, indicating potential challenges in navigation, connectivity, residents’ mobility, accessibility, and safety. The article suggests the importance of re-evaluating the design and planning approaches for these developments to promote organic townscape growth to ensure smooth integration with the surroundings. Full article

It is not unusual for government reports to place spatial inequalities into a league table, highlighting poorly performing jurisdictions in some form of yardstick competition. A case in point is long-term dwelling vacancies. Action on Empty Homes, which works closely with local governments in the UK, provides commentary about poor performance, including recording persistently higher rates in certain regions and mentioning the worst rankings at the local level. How the distribution of vacant dwellings changes is not well explored. How rigid this league is has been a feature of a discussion in the growth literature. A useful dynamic policy measure in this regard is how far the average jurisdiction changes its league position over a given period. A type of convergence proposed here, implied by Sala-i-Martin, features the time for the initial rankings to become discordant with the current order. One could see this sort of measure being used widely, wherever performances are judged relatively as a means of highlighting good practice. Using English data on vacant dwellings, this paper shows that there is a ‘long memory’ in long-term vacancy rates, both at the local and regional levels. The industrial and housing inheritances of districts in the North of England, evident in the league table in 2004, remain influential after 18 years, even with general population growth. Although the use of incentives to bring dwellings back into use is thought to be successful, it is suggested that the role of the buy-to-let investor may have been overlooked. Changes in the treatment of their rewards appear to coincide with a rise in long-term vacancies. Full article

Greece is experiencing a steady population decline caused by the declining migratory and natural balance. This research investigates the spatial impact of socio-economic and demographic factors on the natural population balance in Greece for the spatial zoning of municipal administrative units. Using geographically weighted regression (GWR) on data from the 2011 Greek census, the research explores the local impacts of factors like housing repair permits, vacant housing, employment rates, population inflows, distance from regional centers, aging, gender ratios, and education levels. An initial ordinary least squares (OLS) regression was conducted, revealing significant spatial variation and emphasizing the necessity of spatial econometric methods. The GWR model proved to be more effective in accounting for the variance in the data, removing spatial autocorrelation and revealing high local variation. Results show the high negative impact of the aging index in Western Greece and the Ionian islands, the counterintuitive positive effect of the gender ratio in urban areas, and the positive influence of population inflows in high-migration regions like Northern Greece and Crete. The results of this study underline the need to utilize spatial econometric methods for a precise and detailed understanding of demographic trends and provide valuable insights for localized strategies to address demographic challenges. Full article

This article provides a comprehensive analysis of depopulation and residential dynamics in Teruel, a province emblematic of the aging and depopulation issues prevalent in many inland regions of Spain and Europe. Through an in-depth examination utilizing official statistics, academic studies, and reports, this study highlights the demographic structure, historical evolution, and current trends in Teruel. Key patterns of population change and their implications for urban and rural planning are identified. The analysis covers population density, vital balances, and household distribution, with a special focus on the significant role of the foreign population. Additionally, the challenges associated with vacant housing and the management of unused land are discussed, proposing revitalization strategies for the built environment in rural settings through sustainable housing initiatives. This study aims to contribute to the discourse on sustainable development of small cities and rural areas, offering integrated solutions that not only enhance living conditions but also encourage balanced and sustainable growth. Full article

The House Sparrow (Passer domesticus) is a common but declining bird species in its native urban areas, partly due to reduced nesting site availability caused by modern urbanisation and loss of old architectural styles. In this study, we analysed, through a multivariate approach, the environmental factors influencing House Sparrow nest site selection in three diverse inland urban areas within the Valencian Community, Spain. We located 584 House Sparrow nests during spring 2017 and also selected 300 random points (habitat availability) in the study localities. We used Factorial Analyses of Mixed Data to assess urban feature gradients of nests and urban variables. We carried out Generalized Linear Mixed Models to compare nest locations to random points and explore variations in nesting typologies between urban zones. Specific nest site preferences vary between urban sectors, indicating that House Sparrow nests are not randomly located in urban areas. Nests are typically found near parks, schools, vacant plots, city limits, and surrounding crops, where greater vegetation cover provides abundant food sources. Low-rise terraced houses with traditional roofs and open clay tiles are consistently preferred for nesting, whereas modern architectural trends reduce nesting opportunities. Preserving green areas and old architecture with open clay tiles is essential for maintaining nesting sites and promoting House Sparrow conservation in Mediterranean urban areas. Adherence to these conservation measures may also benefit other hole-nesting species and urban wildlife reliant on green spaces. Full article

The number of vacant houses in Japan has increased rapidly in recent years due to a declining population. The government has been actively developing measures to solve the vacant house problem and has implemented subsidy programs to support the expansion of vacant house utilization projects. Japan has a particularly high number of vacant houses that are utilized for the purpose of “tourism”. However, vacant house utilization projects are scattered across Japan, and information on such projects is lacking. Moreover, the correlation between different vacant house utilization projects and their location characteristics has not been investigated. In this study, we used a travel information website to extract vacant house utilization facilities from the locations listed and determined the location characteristics of the utilization facilities. We classified the extracted utilization facilities into different categories and used the k-means method to group vacant house utilization facilities according to their categories and regional characteristics. The results obtained in this study can help local governments and businesses implement appropriate location-specific utilization projects. Full article

This study uses time series regression models and dynamic panel models of five-class housing to investigate the dynamics of the housing price-vacancy relationship in Hong Kong, offering insights distinct from previous cross-sectional analyses that take new housing completions as a supply proxy, without considering vacant homes as a source of housing supply. Two major contributions emerge: first, the results support the hypothesis that housing vacancies exert a negative impact on housing prices, holding other factors constant. Second, new builds supply is found to have a positive effect on housing prices, which is in line with many previous studies, but it contradicts the prediction. The results challenge the use of land supply or new housing completions as the proxy of housing supply and put forward a novel suggestion of including vacant homes in the housing price analysis. Advanced approaches to collecting housing vacancy data are also discussed. These findings have significant implications for policymakers, urban planners, and real estate investors, providing valuable insights for crafting targeted interventions and informing investment decisions. This is one of the first time series and dynamic panel analyses of housing vacancy’s effect on prices. Full article

In the last decades, historic European cities such as Lisbon have faced the challenge of aging dwellings, infrastructures, and a growing number of vacant buildings. These vacant spaces represent both a problem and an opportunity for the cities. While they detract from the city’s aesthetics and safety, they also offer a chance for renewal. Strategic reuse can address housing shortages, boost businesses, and revitalize neighborhoods. This study examines Lisbon’s efforts to revitalize vacant buildings from 2009 to 2022, with projections extending into the next five to ten years. Analyzing data on building use and reoccupation, the study reveals significant progress. A detailed survey of 1674 vacant buildings in 2009 shows many have been transformed. Then, through a GIS-based analysis, the immediate social and economic impacts of the requalification process are assessed, and two future development scenarios are evaluated. By 2022, 60% of these buildings (999) were reoccupied, expanding housing options and driving economic growth. Shops saw a 166% increase in occupancy, highlighting a thriving commercial sector. Additionally, 27% of the reoccupied buildings now hold tourism activities, including short-rental accommodation and hotels. Short- and long-term scenarios are proposed based on a comprehensive survey that captured the status, function, and preservation conditions of the vacant buildings within the city. These scenarios are planning tools for exploring potential future trajectories of urban development, allowing policymakers to anticipate issues, mitigate risks, and make informed decisions, shaping a more sustainable and resilient Lisbon. Full article