Search Results (74)

Over the past three decades, the Yangtze River Delta has undergone a rapid urbanization phenomenon, resulting in pronounced urban sprawl that has significantly impacted regional sustainable development and air quality. This study constructs an urban sprawl index based on nighttime light data spanning 2000–2020 and employs exploratory spatio-temporal analysis, panel data models, and spatial econometric models to examine the evolution of urban sprawl and its effects on PM_2.5 concentrations. The results reveal four key findings: (1) Urban sprawl is spatially heterogeneous, exhibiting a ‘high in the centre-east, low in the north-west’ pattern, with high-intensity sprawl expanding from the central region towards the north-west and south-west; (2) The dominant growth pattern is characterized by relatively rapid expansion. The global Moran’s I index fluctuates between 0.428 and 0.214, indicating a gradual decline in the global clustering effect of urban sprawl. Meanwhile, the share of local high–high agglomeration zones decreases to 21.9%, whereas low–low zones increase to 24.3%; (3) Spatio-temporal transitions of urban sprawl show strong spatial dependence while overall relocation exhibits inertia; (4) Before the implementation of the Ten Key Measures for Air Pollution Prevention and Control in 2013, urban sprawl significantly intensified PM_2.5 pollution. Following the policy, this relationship notably reversed, with sprawl exhibiting pollution-mitigating effects in certain regions. The spatial diffusion of pollution is evident, as urban sprawl influences air quality through both local development and inter-regional interactions. This study provides an in-depth analysis of the spatio-temporal evolution of urban sprawl and establishes a framework to examine the interactive mechanisms between urban expansion and air pollution, thereby broadening perspectives on atmospheric pollution research and offering scientific and policy guidance for sustainable land use and air quality management in the Yangtze River Delta. Full article

The social-ecological resilience of rural settlements refers to their ability to resist and mitigate the risks posed by internal and external disturbances, and to utilize the external environment to achieve a new equilibrium state. Amid rapid urbanization, it is of great significance for mountainous settlements to improve their risk resistance and development ability. Taking Dong’an Town in Chengkou County, located in the eastern part of Qinling–Bashan Mountains in southwestern China, as the research object, this study constructs an evaluation index system for rural residential resilience based on social-ecological resilience theory. It explores the resilience level of rural residences in mountainous areas from the dimensions of internal resilience and external environmental resilience and scientifically proposes an optimization path for the spatial layout of rural residences. This study provides a reference for optimizing the rural living environment, promoting spatial equity, and improving people’s livelihood according to local conditions. The results showed that: (1) The overall level of security resilience of rural settlements in Dong’an Town was relatively high, with 221 patches above the security level, accounting for 19.53% of the total area of the town. (2) The rural residents in Dong’an Town can be categorized into three types: core structure optimization, peripheral system upgrading, and relocation and withdrawal. Different types of rural settlements adapt to internal and external resource conditions and select optimal spatial layout paths according to local conditions. Full article

Rapid socio-spatial change in China’s traditional villages threatens living heritage and weakens locally grounded identity. This paper theorizes place identity as a dynamic, embodied and performative ecology and examines it in Dali Dong Village across four dimensions, emotional attachment, symbolic meaning, continuity and behavioural commitment, using a triangulated qualitative design that integrates interviews, spatial observation and visual ethnography. Findings show that identity is enacted around ritual architectures and everyday settings, particularly the Drum Tower, Flower Bridge, and Sa altar. Emotional attachment and symbolic meaning are expressed consistently across sources, whereas continuity and behavioural commitment are uneven, shaped by ritual fatigue (compressed rehearsal windows), symbolic commodification under tourism, and selective continuity in intergenerational transmission. These mechanisms identify where the identity fabric is most fragile and where intervention leverage lies. Conceptually, the study relocates place identity from cognition-centred, urban models to ritualized rural lifeworlds. Practically, it offers a portable framework for community-anchored stewardship that can be adapted to similar settlements and aligned with policy aims for safeguarding living heritage. Full article

Residential mobility is not only a demographic process but also a mechanism that reshapes urban form, economic vitality, and spatial inequality. In South Korea, where rapid population decline and stark regional disparities pose urgent planning challenges, analyzing the determinants of residential in-migration provides critical insights into how cities and regions adapt to these demographic shifts. This study addresses the questions of why individuals relocate and how migration drivers vary across regional typologies and age cohorts. Using a Negative Binomial Regression framework applied to spatially disaggregated migration data, this study identifies several key patterns. Housing prices, population density, and network centrality consistently act as strong and positive predictors of in-migration across regions and cohorts. Even shrinking cities retain attractiveness through density, likely reflecting service accessibility and agglomeration benefits. Employment opportunities, school proximity, and road network density play crucial roles in peripheral regions. Katz centrality strongly shapes decisions among younger populations (≤39), while older adults (65+) prefer areas with lower economic intensity and better access to public transportation. These findings advance theoretical understandings of residential mobility and offer policy-relevant insights for age-sensitive and regionally differentiated urban planning. Full article

Rapid urban expansion has led to an increasing number of people relocating to Urban–Rural Fringe Areas (URFAs) in China, with related development placing pressure on ecosystems in these locations. Community parks (CPs) are a key category of urban public park (UPPs) in Chinese planning and play a vital role in improving residents’ quality of life and enhancing regional environment, whilst also promoting sustainable urban development. Consequently, CPs are considered by many to be integral components of “communities” in Chinese cities. Drawing on documentary analysis and field research, this paper explores the socio-economic and ecological values associated with CP investments in URFAs in China. It assesses governmental policies and expert perspectives concerning CPs’ development in URFAs and analyses the factors influencing their planning and delivery. The research highlights how policy and stakeholders’ viewpoints impact the development of sustainable green space in URFAs. To enhance the construction of multi-functional CPs in URFAs, we propose a series of characteristics that need to be considered in future developments, including stakeholder engagement, resident needs, and park design. These insights offer an evidence-based reference for decision-makers, aiming to better meet the requirements of residents and support the development of urban sustainability. Full article

The impact of urbanization on the agricultural economy has long attracted scholarly attention. Taking China as a case, this study investigates the relationship between urbanization and agricultural development under the dual progress of urbanization and the rural revitalization strategy. Based on panel data from 31 mainland provinces, this paper measures agricultural economic efficiency using the global slack-based measure (SBM) model and employs quantile regression to systematically analyze the influence of various urbanization factors across different levels of agricultural efficiency. A Tobit regression model is further adopted for robustness checks. The results show that representative urbanization factors, such as the proportion of urban population and the prevalence of higher education, exert significant negative impacts on agricultural efficiency, particularly in regions with higher efficiency levels. Freight volume has a significantly negative effect in regions with medium and low efficiency, while freight turnover negatively impacts medium- to high-efficiency areas. In contrast, improvements in healthcare services and digital infrastructure are found to consistently enhance agricultural efficiency. Although the corporatization of agriculture is often regarded as a key outcome of urbanization, its efficiency-improving effect is not statistically significant in most models and is mainly concentrated in high-efficiency regions. Overall, the improvement in China’s agricultural economic efficiency relies more on direct support from the rural revitalization strategy, while rapid urbanization has failed to bring substantial benefits and has even led to structural negative effects. These adverse outcomes may stem from the rapid occupation of suburban farmland, increased logistics costs due to the relocation of agricultural activities, and the ineffective absorption of surplus rural labor. This study highlights the need for future urbanization policies in China to pay greater attention to the coordinated development of the agricultural economy. The methods and findings of this research also provide reference value for other developing regions facing similar urbanization-agriculture dynamics. Full article

This study examines the relationship between K-Pop and education migration to South Korea in the context of the global internet and the COVID-19 pandemic. It focuses on the phenomenon in which local Asian territories have been widely influenced by the Korean Wave, particularly K-Pop, even during the era of global communication and health risks. This research illuminates some intriguing aspects of the distinctive reception patterns of Korean Wave audiences, as well as their unique characteristics, such as innocence, transgression, and the nuanced dynamics of the fandom during that period. Furthermore, this research engages critically with controversial aspects of cultural politics, such as the transmission of the legacy of K-Pop and the centralisation of femininity more actively. This study concludes that K-Pop has recently been relocated to the conjunctures of mediated and overdetermined influences on students’ education migration to South Korea rather than acting as a direct power and reason for it, particularly in the context of the COVID-19 pandemic and the rapid digitalisation of education. Full article

Considering the rapid integration of digital services into daily life, it is crucial to analyze the impacts of the substitutability of physical services with digital alternatives. Limited studies have been conducted to investigate the relationship between service substitution and social networks and assess their impact on urban structure. Therefore, this study fills the gap by investigating how digital service substitution and social networks influence residential location choices and urban structure, aiming to support future sustainable urban modeling and planning tools. The study, through a comprehensive analysis incorporating cluster analysis, factor analysis, and binomial logistic regression on a web-based questionnaire survey (n = 6210), finds that socio-demographic factors significantly influence digital alternatives, and that digital service substitution and social networks impact sustainable urban structure. Younger individuals showed significantly higher adoption of digital alternatives, with age negatively associated with relocation likelihood. In urban areas, each additional year of age reduces the likelihood of relocation by approximately 4.4%, and individuals with high shopping substitution are 3.12 times more likely to consider relocation. These findings suggest that urban planners and policymakers to balancing physical and digital service provision to maintain a higher quality of life aligned with the SDGs and ensure sustainable urban development. Full article

With the rapid development of lightweight unmanned aerial vehicles (UAVs), the combination of UAVs and ground-moving target indication (GMTI) radar systems has received great interest. However, because of size, weight, and power (SWaP) limitations, the UAV may not be able to equip a highly accurate inertial navigation system (INS), which leads to reduced accuracy in the moving target relocation. To solve this issue, we propose using an image registration algorithm, which matches a Doppler beam sharpening (DBS) image of detected moving targets to a synthetic aperture radar (SAR) image containing coordinate information. However, when using conventional SAR image registration algorithms such as the SAR scale-invariant feature transform (SIFT) algorithm, additional difficulties arise. To overcome these difficulties, we developed a new image-matching algorithm, which first estimates the errors of the UAV platform to compensate for geometric distortions in the DBS image. In addition, to showcase the relocation improvement achieved with the new algorithm, we compared it with the affine transformation and second-order polynomial algorithms. The findings of simulated and real-world experiments demonstrate that our proposed image transformation method offers better moving target relocation results under low-accuracy INS conditions. Full article

With the rapid development of lightweight unmanned aerial vehicles (UAVs), the combination of UAVs and ground moving target indication (GMTI) radar systems has received great interest. In GMTI, moving target relocation is an essential requirement, because the positions of the moving targets are usually displaced. For a multichannel radar system, the position of moving targets can be accurately obtained by estimating their interferometric phase. However, the high position accuracy requirements of antennas and the computational resource requirements of algorithms limit the applications of relocation algorithms in UAV-borne GMTI radar systems. In addition, the clutter’s interferometric phase can be severely affected by the undesired phase error in the site. To overcome these issues, we propose an improved knowledge-based (KB) algorithm. In the algorithm, moving targets can be relocated by comparing their interferometric phase with the clutter’s phase. As for the undesired phase error, the algorithm first employs a random sample consensus (RANSAC) algorithm to iteratively filter the outliers. Compared with other classic relocation algorithms, the proposed algorithm shows better relocation accuracy and can be applied in real-time applications. The performance of the proposed improved KB algorithm was evaluated using both simulated and real experimental data. Full article

Background: Facility location is a key challenge in humanitarian logistics, particularly in disaster response, where rapid and efficient resource deployment is crucial. Temporary facilities offer a cost-effective solution due to their rapid deployment and flexibility in addressing increased demand and the dynamic conditions of post-disaster environments. Methods: This study conducts a systematic literature review following PRISMA guidelines to analyze facility location problems involving temporary or modular facilities in humanitarian logistics. A total of 65 articles from Scopus and Web of Science were analyzed. Results: Most studies focus on temporary facilities like shelters and medical centers in earthquake-affected areas, with most applications in Asia. Despite being temporary, only 6% of the studies consider closure decisions. Recent research explores modular facilities that enhance adaptability through module relocation and capacity adjustments. Conclusions: Temporary facilities after sudden-onset disasters require advanced modeling approaches that include multi-period planning, modular design, and complex decision-making, requiring solutions through heuristics or relaxations. However, there is a lack of research on their application in slow-onset and human-induced disasters. Moreover, considering geographical, cultural, and political factors is essential to ensure effective solutions. Further studies are also needed on facilities functioning as collection and processing centers, given their critical role in the humanitarian supply chain. Full article

Amid accelerating globalization and resource scarcity, rapid urbanization and population mobility have made sustainable development a critical issue for cities. Frequent relocations pose furniture disposal challenges for many young migrants, with high transportation costs and furniture wear increasing their economic burden and resource waste. Origami design effectively addresses these needs with its portability, easy storage, simplified manufacturing, and reduced failure rates. However, most furniture designers lack origami expertise, limiting their ability to leverage these benefits. This study integrates the existing literature and presents a sustainable furniture design method combining Rhinoceros 3D, Grasshopper, and Crane, enabling designers to incorporate origami principles with limited prior knowledge. The results show that this method not only enhances the economic feasibility of furniture but also balances user needs, commercial interests, and environmental sustainability, offering new insights for urban sustainable development. Full article

This study presents an innovative automatic scheduling method for the relocation of customs inspection vehicles, leveraging Vehicle Electronic Identification (EVI) and biometric recognition technologies. With the expansion of global trade, customs authorities face increasing pressure to enhance logistics efficiency. Traditional vehicle scheduling often relies on manual processes and simplistic algorithms, resulting in prolonged waiting times and inefficient resource allocation. This research addresses these challenges by integrating EVI and biometric systems into a comprehensive framework aimed at improving vehicle scheduling. The proposed method utilizes genetic algorithms and intelligent optimization techniques to dynamically allocate resources and prioritize vehicle movements based on real-time data. EVI technology facilitates rapid identification of vehicles entering customs facilities, while biometric recognition ensures that only authorized personnel can operate specific vehicles. This dual-layered approach enhances security and streamlines the inspection process, significantly reducing delays. A thorough analysis of the existing literature on customs vehicle scheduling identifies key limitations in current methodologies. The automatic scheduling algorithm is detailed, encompassing vehicle prioritization criteria, dynamic path planning, and real-time driver assignment. The genetic algorithm framework allows for adaptive responses to varying operational conditions. Extensive simulations using real-world data from customs operations validate the effectiveness of the proposed method. Results indicate a significant reduction in vehicle waiting times—up to 30%—and an increase in resource utilization rates by approximately 25%. These findings demonstrate the potential of integrating EVI and biometric technologies to transform customs logistics management. Additionally, a comparison against state-of-the-art scheduling algorithms, such as NSGA-II and MOEA/D, reveals superior efficiency and adaptability. This research not only addresses pressing challenges faced by customs authorities but also contributes to optimizing logistics operations more broadly. In conclusion, the automatic scheduling method presented represents a significant advancement in customs logistics, providing a robust solution for managing complex vehicle scheduling scenarios. Future research directions will focus on refining the algorithm to handle peak traffic periods and exploring predictive analytics for enhanced scheduling optimization. Advancements in the intersection of technology and logistics aim to support more efficient and secure customs operations globally. Full article

This research addresses the rapid aging phenomenon prevalent in Asian societies, which has led to a significant increase in elderly individuals relocating to nursing homes due to health-related issues. This trend has resulted in social isolation and loneliness among the elderly, contributing to physical and mental ailments such as hypertension and cardiovascular diseases, as highlighted by the World Health Organization (WHO). To mitigate these issues, the research proposes leveraging technology, specifically the integration of robotics, to alleviate the caregiver shortage and enhance human interaction for the elderly. The novel approach involves developing a social robot designed to bridge the gap between humans and machines, combining knowledge from embedded systems, robotics, and essential soft skills for effective interaction. The authors found that this technological solution holds promise in addressing the caregiver shortage and improving the well-being of elderly individuals by reducing their sense of isolation, fostering better mental and physical health outcomes, and potentially transforming the landscape of elderly care through innovative technological applications. Future work includes expanding pilot studies and collaborating with healthcare institutions to further validate the effectiveness of the solution. Full article

Rapid growth rate indicates that the free-floating electric vehicle sharing (FFEVS) system leads to a new carsharing idea. Like other carsharing systems, the FFEVS system faces significant regional demand fluctuations. In such a situation, the rental stations and charging stations should be constructed in high-demand areas to reduce the scheduling costs. However, the planning of the FFEVS system includes a series of aspects of rental stations and charging stations, such as the location, size, and number, which interact with each other. In this paper, we first provide a method for forecasting the demand for car sharing based on the land characteristics of Beijing FFEVS station catchment areas. Then, the multi-objective MILP model for planning FFEVS systems is developed, which considers the requirements of vehicle relocation and electric vehicle charging. Afterward, the capabilities of the proposed models are demonstrated by the real data obtained from Beijing, China. Finally, the sensitivity analysis of the model is made based on varying demand and subsidy levels. From the results, the proposed model can provide decision-makers with useful insights about the planning of FFEVS systems, which bring great benefits to formulating more rational policies. Full article