Rural-urban Fringe Research Articles

Multi-species ecological network based on asymmetric movement: Application in an urban rural fringe

Ecological network (EN) is a popular approach for biodiversity conservation, which aims to facilitate animal movement between habitats. However, asymmetric movement caused by the subjectivity of animals and environment heterogeneity is seldom considered in EN design. To design EN based on asymmetric movement, an individual-based model, PDArunner, is developed, which can identify corridors based on explicit movement paths. Since the urban–rural fringe is susceptible to landscape change, a multi-species EN based on asymmetric movement is designed for Jinnan district, Tianjin, China by simulating movement of Mustela sibirica, Spilopelia chinensis and Gallinula chloropus using PDArunner. Asymmetric movement is partitioned based on the size of departure and arrival habitats. Asymmetric corridors are thus identified based on movement in particular direction. In Jinnan, successful transfer rate of focal species from small to large habitat increases with difference in habitat size. The spatial extent of asymmetric corridors is more concentrated for G. chloropus. There are more corridors from large to small habitats than in the opposite direction, especially for S. chinensis and G. chloropus. There are more one-way corridors for S. chinensis and G. chloropus than M. sibirica. Perceptible high vegetation coverage places with large enough contrast to environment are suggested to be consecutive within 50 m for M. sibirica in Jinnan, which also benefits S. chinensi. G. chloropus can benefit from well-conserved water quality and quantity. A cross-administration collaboration is also highlighted for large scale conservation.

The Mediating Effect of Urban-Rural Fringe in the Interaction Between Urbanization and Ecosystem Health

The Mediating Effect of Urban-Rural Fringe in the Interaction Between Urbanization and Ecosystem Health

A Scene–Object–Economy Framework for Identifying and Validating Urban–Rural Fringe Using Multisource Geospatial Big Data

Rapid urbanization has led to the emergence of urban–rural fringes, complex transitional zones that challenge traditional urban–rural dichotomies. While these areas play a crucial role in urban development, their precise identification remains a significant challenge. Existing methods often rely on single-dimensional metrics or administrative boundaries, failing to capture the multi-faceted nature of these zones. This study introduces a novel “Scene–Object–Economy” (SOE) framework to address these limitations and enhance the precision of urban–rural fringe identification. Our approach integrates multisource geospatial big data, including remote sensing imagery, nightlight data, buildings, and Points of Interest (POI), leveraging machine learning techniques. The SOE framework constructs feature from three dimensions: scene (image features), object (buildings), and economy (POIs). This multidimensional methodology allows for a more comprehensive and nuanced mapping of urban–rural fringes, overcoming the constraints of traditional methods. The study demonstrates the effectiveness of the SOE framework in accurately delineating urban–rural fringes through multidimensional validation. Our results reveal distinct spatial patterns and characteristics of these transitional zones, providing valuable insights for urban planners and policymakers. Furthermore, the integration of dynamic population data as a separate layer of analysis offers a unique perspective on population distribution patterns within the identified fringes. This research contributes to the field by offering a more robust and objective approach to urban–rural fringe identification, laying the groundwork for improved urban management and sustainable development strategies. The SOE framework presents a promising tool for future studies in urban spatial analysis and planning.

The emerging middle ground: A case study of vernacular Hakka settlements in the peri-urban areas of southern China through an architectural heritage analysis

Rapid urban expansion is transforming rural areas globally, prompting scholars to challenge the traditional urban-rural dichotomy and focus on transitional zones such as the rural-urban fringe and peri-urban areas. This article documents the evolution of architectural morphology in traditional Hakka settlements in peri-urban areas of southern China and coins the hybrid architectural landscape combined with urban and rural characteristics in these ambiguous territories as the “Middle Ground.” Fieldwork was conducted in four Hakka villages in Heyuan, northeast Guangdong, China, between 2021 and 2023. An explorative case study was employed to analyze the architectural morphology of the Middle Ground by mapping village fabric, dwellings, and street markets through aerial photography. A participatory perspective was also incorporated, involving observation, interviews, and documentation of the daily life of local villagers. This research examines how authority and mobility have shaped the Middle Ground, potentially leading to a state of “placelessness,” and explores the role of rural heritage in this context. This research contributes to the broader discourse on peri-urban areas by offering an architectural heritage atlas as an addition to existing research.

The first discovery of severe fever with thrombocytopenia virus in the center of metropolitan Beijing, China

Severe fever with thrombocytopenia virus (SFTSV), an emerging tick-borne bandavirus, poses a significant public health threat in rural China. Since 2021, an increase of local cases has been noted in the rural-urban fringe of Beijing. This study aimed to assess the formation of natural foci in urban areas by conducting a field survey of ticks and hedgehogs from the second to fifth ring roads of Beijing. Our survey revealed a diverse tick population in city parks, including the major SFTSV vector, Haemaphysalis longicornis. Parthenogenetic H. longicornis, known for its role in the rapid spread of SFTSV, was identified in key locations such as Beihai Park and Taoranting Park, near the Forbidden City. Notably, high SFTSV seroprevalence and RNA prevalence were found in hedgehogs and parasitic ticks in the center of Beijing. Phylogenetic analyses of SFTSV RNA and mitochondrial sequences of parthenogenetic H. longicornis ticks revealed the existence of diverse lineages of SFTSV and H. longicornis ticks within Beijing, suggesting multiple invasion events happened. These findings reveal the circulation of SFTSV in central Beijing, highlighting the need for urgent attention and enhanced surveillance measures.

Identification and Spatiotemporal Evolution Analysis of the Urban–Rural Fringe in Polycentric Cities Based on K-Means Clustering and Multi-Source Data: A Case Study of Chengdu City

Urban fringe areas, serving as transitional zones between urban and rural landscapes, are characterized by their transitional nature, high dynamics, and spatial heterogeneity. Identifying the extent of an urban–rural fringe (URF) and analyzing its evolutionary characteristics are crucial for urban planning and development. However, limited research exists regarding the identification of a URF and the analysis of its spatiotemporal evolution in polycentric cities. Using Chengdu as a case study, this research employed the K-means clustering method to identify the spatial extent and evolution patterns of the URF in Chengdu from 2010 to 2020 based on the spatiotemporal characteristics of multi-source data. The results indicate that (1) the K-means clustering method can reasonably and efficiently identify URF in polycentric cities; (2) Chengdu exhibited a polycentric urban structure with a “main center-subcenter” pattern, where the URF was adjacent to the main and subcenters, assuming an overall annular wedge shape; (3) there was a significant expansion of the URF in the northeast–southwest direction from 2010 to 2020, accompanied by substantial land use changes. The evolution of the URF was driven by the dual mechanisms of urban suburbanization and rural urbanization, exhibiting characteristics such as singular urban functions, dispersed and chaotic land use, fragmented landscapes, and increasing complexity. This study extended the research on URFs, aiding in the understanding of urban spatial growth patterns and providing decision support for the integrated development of urban and rural areas.

The Effect of Urban–Rural Fringe Landscape Environment Enhancement on the Settlement Intentions of Young Talents

As new urbanization and rural revitalization strategies are implemented, the relationship between urban and rural areas is rapidly changing. Accordingly, rural landscape design is becoming increasingly important for promoting rural development. Located at the intersection of urban and rural areas and offering unique geographic characteristics and developmental potential, urban–rural fringe villages offer a valuable setting for assessing how rural transformation and landscape improvement influence the settlement intentions of regional talents. Drawing upon the Landscape Affordance Theory and the Stimulus–Organism–Response Theory, this study develops a model to evaluate how enhancements in comfort, convenience, safety, and aesthetics within rural landscapes influence the perceptions of livability and settlement intentions of young rural talents. The research utilizes a survey of residents aged 16 to 45 in representative urban–rural fringe villages in Nanjing, Jiangsu Province, collecting 230 valid responses. Data analysis was performed using SPSS 26 and AMOS 28 to assess the impact of these landscape attributes on livability perceptions and settlement intentions. This study demonstrates that Perceived Convenience (PCV) and Perceived Aesthetics (PA) have significant positive effects on Design Satisfaction (DS) and Perceived Livability (PL). The research identifies the positive impacts of the four characteristics of rural landscape enhancement on PL, ranking them in order of influence: PCV > PA > Perceived Safety (PS) > Perceived Comfort (PC). Similarly, the positive effects on DS are ranked as follows: PCV > PA > PC. PL is identified as having the strongest impact on Talents’ Intention to Stay (TIS), indicating that improving livability perceptions is crucial for enhancing both design satisfaction and settlement intentions. Our findings demonstrate that improvements to the convenience, comfort, aesthetics, and safety of the landscape environment can significantly affect the settlement intentions of young talents in rural areas. Through field research and empirical data validation, this study highlights the positive effect of enhancements in four key areas of landscape design on the perceived livability and settlement intentions of young talents in rural settings, offering clear guidance for rural planning and design initiatives.

Dietary habit and lifestyle of postpartum women in South China: a mixed methods research

ObjectiveTo investigate the dietary and hygiene behaviours and influencing factors of women during the puerperium in South China.DesignA cross-sectional study.SettingThree tertiary hospitals in Guangdong Province, ChinaParticipantsFrom November 2022 to March...

Evolution Process and Land Use/Land Cover Response of Urban–Rural Space in Wuhan under Polycentric Structure

Polycentric development facilitates urban–rural spatial reshaping and land use/land cover (LULC) protection. Previous studies have predominantly focused on urban areas, with spatial delineation methods biased towards the macro-level, lacking a holistic perspective that situates them within the urban–rural spatial framework. This study proposes a spatial delineation framework that is applicable to the polycentric structure, taking into account the social, economic, and natural characteristics of urbanization. It employs semivariance analysis and spatial continuous wavelet transform (SCWT) to analyze the effects of polycentric development on the urban–rural space of Wuhan from 2012 to 2021 and applies a land use transition matrix, landscape indices, and bivariate spatial autocorrelation to quantify the responses and differences of LULC within urban–rural space. The results indicate that 600m×600m is the best scale for exhibiting the multidimensional characterization of urbanization. The polycentric structure alleviates the compact development of the central city, and it drives rapid expansion at the urban–rural fringe, exacerbating the spatial heterogeneity in LULC change pattern, spatial configuration, and urbanization response within urban–rural spaces. The overall effects of urbanization on LULC are relatively weak along the urban–rural gradient, experiencing a transition from positive to negative and back to positive. This study employs a novel spatial delineation framework to depict the polycentric transformation of metropolitan areas and provides valuable insights for regional planning and ecological conservation in the urban–rural fringe.

Research and analysis of urban-rural residential carbon emissions in China

Residential carbon emissions are an important component of anthropogenic carbon emissions. a significant increase in residential carbon emissions has become a reality under the global urbanization process. In this context, this paper built a feature combination value model based on NPP-VIIRS nighttime light remote sensing data, and divided urban-rural areas through breakpoint analysis method and reference comparison method. Then, explored the characteristics and differences of residential carbon emissions and per capita residential carbon emissions in nine different levels of cities in 2019 from the perspective of urban-rural areas. The results indicate that the residential carbon emissions and per capita residential carbon emissions shows the spatial distribution characteristics of first tier cities>second tier cities>third tier cities. Among them, the residential carbon emissions in Beijing, Guangzhou, Nanjing, Taiyuan show a distribution pattern of urban>urban-rural fringe>rural. The residential carbon emissions in Shijiazhuang, Wuxi, Xiangyang, Zunyi, Huai’an show a distribution pattern of rural>urban-rural fringe>urban. The per capita residential carbon emissions of urban areas are relatively low, while the per capita residential carbon emissions of rural areas are relatively high, show a distribution pattern of rural>urban-rural fringe >urban. The results can help the Chinese government balance the needs of urban-rural development in different levels of cities, so as to formulate targeted carbon emission reduction policies and achieve low-carbon goals.

Distribution and Risk Assessment of VOCs in Road Dust Across Different Urban Areas

ABSTRACT Volatile organic compounds (VOCs) are significant pollutants in urban road dust, but their distribution and associated health risks remain unclear. VOC distribution in road dust from six distinct urban areas in Beijing Daxing District, China was systematically investigated. Eighteen VOCs were detected, with the highest load in commercial areas (7.73 μg/g), followed by industrial parks (6.38 μg/g), residential areas (3.35 μg/g), leisure areas (2.79 μg/g), traffic areas (2.01 μg/g) and urban-rural fringe (1.85 μg/g), much lower than in air and water phases. Typical VOCs in road dust include methyl tertiary butyl ether (MTBE) (0.82–1.24 μg/g), benzene series compounds (0.02–4.19 μg/g) and volatile halogenated alkanes (0.002-0.095 μg/g). Incomplete combustion of road vehicle fuels is the key source of VOCs. Particular attention was given to VOCs in typical sites within the urban-rural fringe, known for their unique pollution characteristics. The VOCs loads were ranked as follows: Gas Stations (2.61–2.62 μg/g) > Intersection (1.41 μg/g) > Main Road (1.34 μg/g) > University Gate (1.27 μg/g). Increased vehicle activity and frequent stalling contribute to higher VOCs accumulation in road dust. Health risk assessment indicates there is no appreciable non-carcinogenic risk associated with exposure to road dust VOCs. Further research should consider VOCs in the broader environmental context, including air and water.

Meta-analysis of Heavy Metal Pollution in Soil-crop Systems in China's Urban-Rural Fringe

Owing to the influence of human activities, the issue of heavy metal pollution in farmland soil at the urban-rural fringe has become increasingly prominent. An accurate understanding of the characteristics of soil-crop heavy metal pollution in these areas is of great significance for ensuring food safety and promoting social sustainable development. Most of the existing studies rely on small-scale field monitoring, but research at the national level has not effectively captured the unique pollution dynamics of this urban-rural interface. Based on the published literature, the present study investigated the status of heavy metal pollution in the soil-crop system within China's urban-rural fringe through Meta-analysis. On this basis, the study evaluated the risks to human health associated with heavy metals in major crops in a given region. The results showed that heavy metals were accumulated in farmland soil in the urban-rural fringe of China, especially in Cd （Igeo = 0.89） pollution, and its distinct spatial heterogeneity patterns emerged. When considering different types of cultivated land, paddy fields and irrigated land exhibited a higher tendency of heavy metal accumulation. From the varying urbanization levels, the accumulation of heavy metals in soils of small and medium-sized cities was more obvious. For crops in the urban-rural fringe, Cd and Pb had the highest exceedance rate in rice （28.25% and 39.64%） and wheat （27.72% and 42.72%）. The health risk assessment results of heavy metals in crops showed that Cd was the main element that posed human health risks, which had some degree of non-carcinogenic risk and unacceptable carcinogenic risk to both children and adults.

Job burnout and its influencing factors among primary healthcare workers during the COVID-19 epidemic in Guangzhou, China, 2021–2022: from the perspective of institutional operation and management

BackgroundThe purpose of this study was to explore the job burnout of primary healthcare workers in Guangzhou during the prevention and control of COVID-19 epidemic and its influencing factors from the perspective of institutional operation and management in 2021–2022.MethodsA cross-sectional study involved 866 primary healthcare workers from different districts of Guangzhou, China. The Chinese version of the Maslach Burnout Inventory-General Survey (MBI-GS) was utilized to assess job burnout. From the perspective of organizational operation and management, the possible causes of job burnout among primary healthcare workers during COVID-19 have been categorized into 7 major aspects. Univariate and multivariate logistic regression analyses were conducted to identify influencing factors for job burnout in primary healthcare workers.ResultsThe detection rate of job burnout among primary healthcare workers was 78.29%. Men (OR = 2.39) and whose institution was located in urban–rural fringe (OR = 1.56) were more likely to detect job burnout. Conversely, institution heads showed a lower risk of job burnout. From the perspective of institutional operation and management, workers who were not satisfied with personnel management (OR = 2.41), materials and vehicles (OR = 2.89), subsidies and compensation (OR = 2.18), humanistic care (OR = 2.11), superior management (OR = 8.32) were found to have a higher risk of job burnout.ConclusionThe detection rate of job burnout among primary healthcare workers in Guangzhou was relatively high during the period of COVID-19. When there is another sudden major epidemic, the managers of institutions can focus on and deal with the problems related to the operation and management of institutions such as personnel management, materials and vehicles, subsidies and compensation, humanistic care, and superior management, so as to provide logistical support for the workers and alleviate their job burnout.

Characterising the urban–rural fringe area (URFA) in China: a review of global and local literature on urban–rural fringe areas

Urban-Rural Fringe Areas (URFAs) in China have experienced significant change since 1978 due to extensive urban growth and sprawl. This article explores the characteristics of URFAs in China through a scoping review approach. Analysis identifies that URFAs in China possess features that are located in and connected to urban and rural areas, mixed land use, occupied by both urban and rural populations, and driven by changes in social structure, economic development and policy implementation. These findings are consistent with URFAs in a global context, illustrating synergies in academic and practitioner approaches. However, China’s URFAs are unique due to the country’s social structure, topographical diversity, divergent urban diversity and the regional variations that exist within urban development policies and strategies. The article contributes to a better understanding of the characteristics of URFAs in China, providing guidance for future policy to support more effective and sustainable development. This article was published open access under a CC BY licence: https://creativecommons.org/licences/by/4.0/ .

Community trust and decisions in the conversion of agricultural land (Case study: Mulyoagung Village, Indonesia)

<p dir="ltr"><span>Urbanization is caused by a drastic increase in population in an area, thus spurring high demand for space or land, leading to land conversion. The phenomenon of land conversion in rural areas is a reciprocal relationship between urban and rural areas influencing the spread of urbanization to rural areas. Mulyoagung Village, one of the villages in Malang, experiencing significant agricultural land conversion. This research aims to identify the classification of area based on the land conversion. Discussion also made on the beliefs and the demographics that played a role in influencing decisions regarding land conversion. The result revealed that Mulyoagung Village is a secondary rural peri-urban classification located between Malang City and Batu City, experienced a conversion of 24.01% of non-built-up land to built-up land within a period of 20 years (2002-2022). The conversion led to a change from initially rural fringe to urban-rural fringe. This results also supported by SEM-PLS analysis which showed that community demographics are the central construct influencing the decision of farming communities to convert their agricultural land.</span></p>

Evaluating the Spatial Heterogeneity and Driving Factors of Sustainable Development Level in Chengdu with Point of Interest Data and Geographic Detector Model

Over the past few decades, China has undergone the largest and fastest urbanization process in world history. By 2023, Chengdu’s urbanization rate had reached 80.5%, significantly higher than the national average of 66.16%. Studying the urbanization experience of Chengdu is of great significance for optimizing urban planning policies in Chengdu and other cities in China. Although much literature has explored the urbanization process from macro and micro perspectives, studies using a top-down approach to examine urban fringe expansion are relatively scarce. This study first applies the entropy weight method to analyze the spatial-temporal evolution trends of urban development, identifying areas of imbalanced development and prominent issues. Secondly, the K-means machine learning algorithm and nightlight data are used to reconstruct and classify urban regions, and a comparative analysis is conducted with administrative divisions to further identify unreasonable areas in urban spatial distribution and structure. Finally, POI data and the geographical detector method are used to analyze the micro-driving forces in areas of imbalanced development, identifying major limiting factors and solutions. The study found that the gap between urban and rural development in Chengdu is narrowing during the urbanization process, but there is severe differentiation in the second circle of Chengdu, where economic development is accelerating but residents’ happiness is declining. Moreover, analysis based on urban nightlight data and land-use data reveals that the expansion areas on the urban-rural fringe are mainly concentrated in the second circle of Chengdu. Micro-level driving factor analysis found that the western region of the second circle has many but small urban settlements, with a dense road network but scattered functional areas. The eastern region has inefficient and extensive use of construction land. Additionally, the mismatch between student status and household registration has resulted in relatively lagging educational resource development, and high entry barriers have hindered the progress of urbanization, leading to low per capita welfare expenditure. These reasons are the main factors causing the decline in residents’ happiness, and this impact shows significant differences at different temporal and spatial scales. Encouraging innovation in research and development or education can serve as a long-term and effective driving force for promoting sustainable urbanization. This study provides valuable insights for scientifically planning sustainable urban development and promoting the urbanization process.

Habitat Protection in Urban–Rural Fringes through Coordinated Ecological Network Construction and Territorial Planning

Habitat Protection in Urban–Rural Fringes through Coordinated Ecological Network Construction and Territorial Planning

Integrating Risk-Conflict assessment for constructing and optimizing ecological security patterns of Polder landscape in the Urban-Rural fringe

Jianghan Plain is an important grain-producing area in China, and the transformation of the natural environment by the long-term polder activities of the people in this area has created a characteristic polder landscape. After 2000, urbanization has led to the destruction of ecosystems in these polder landscapes, especially in sensitive areas at the urban–rural interface. ESP can help mitigate this threat by systematically identifying and connecting ecologically significant areas to enhance ecosystem stability and sustainability. In this paper, taking Dongxihu Polder as an example, we apply multi-source remote sensing data to develop LER and LUC models. Combining these with MCR model, we construct an ESP for Dongxihu Polder. The study shows that (1) the growth of LER and LUC in Dongxihu Polder is characterized by “strong dynamics, high complexity and weak protection”, which is closely related to the urban expansion of the urban–rural boundary area; (2) Watersheds, woodlands, and farmlands play an important role in controlling LERs and LUCs, so we identified 33 ecologically important source areas that are mainly concentrated in these regions; (3) In this paper, 46 ecological strategic nodes and 16 ecological corridors were extracted to construct the Dongxihu Polder ESP of “one ring, five axes, multiple points and multiple chains”, and suggested specific optimization strategies. The study provides feasible ecological management policy recommendations for the protection as well as sustainable development of Dongxihu Polder.

Glucose Lowering Treatment Patterns in Type 2 Diabetes Mellitus (T2DM) Management: A Real World Study from the Rural-Urban Fringe Zone of Suzhou City, Jiangsu Province

Glucose Lowering Treatment Patterns in Type 2 Diabetes Mellitus (T2DM) Management: A Real World Study from the Rural-Urban Fringe Zone of Suzhou City, Jiangsu Province

Construction of a Predictive Model for Diabetes Mellitus Type 2 in Middle-Aged and Elderly Populations Based on the Medical Checkup Data of National Basic Public Health Service

To establish a universally applicable logistic risk prediction model for diabetes mellitus type 2 (T2DM) in the middle-aged and elderly populations based on the results of a Meta-analysis, and to validate and confirm the efficacy of the model using the follow-up data of medical check-ups of National Basic Public Health Service. Cohort studies evaluating T2DM risks were identified in Chinese and English databases. The logistic model utilized Meta-combined effect values such as the odds ratio (OR) to derive β, the partial regression coefficient, of the logistic model. The Meta-combined incidence rate of T2DM was used to obtain the parameter α of the logistic model. Validation of the predictive performance of the model was conducted with the follow-up data of medical checkups of National Basic Public Health Service. The follow-up data came from a community health center in Chengdu and were collected between 2017 and 2022 from 7602 individuals who did not have T2DM at their baseline medical checkups done at the community health center. This community health center was located in an urban-rural fringe area with a large population of middle-aged and elderly people. A total of 40 cohort studies were included and 10 items covered in the medical checkups of National Basic Public Health Service were identified in the Meta-analysis as statistically significant risk factors for T2DM, including age, central obesity, smoking, physical inactivity, impaired fasting glucose, a reduced level of high-density lipoprotein cholesterol (HDL-C), hypertension, body mass index (BMI), triglyceride glucose (TYG) index, and a family history of diabetes, with the OR values and 95% confidence interval (CI) being 1.04 (1.03, 1.05), 1.55 (1.29, 1.88), 1.36 (1.11, 1.66), 1.26 (1.07, 1.49), 3.93 (2.94, 5.24), 1.14 (1.06, 1.23), 1.47 (1.34, 1.61), 1.11 (1.05, 1.18), 2.15 (1.75, 2.62), and 1.66 (1.55, 1.78), respectively, and the combined β values being 0.039, 0.438, 0.307, 0.231, 1.369, 0.131, 0.385, 0.104, 0.765, and 0.507, respectively. A total of 37 studies reported the incidence rate, with the combined incidence being 0.08 (0.07, 0.09) and the parameter α being -2.442 for the logistic model. The logistic risk prediction model constructed based on Meta-analysis was externally validated with the data of 7602 individuals who had medical checkups and were followed up for at least once. External validation results showed that the predictive model had an area under curve (AUC) of 0.794 (0.771, 0.816), accuracy of 74.5%, sensitivity of 71.0%, and specificity of 74.7% in the 7602 individuals. The T2DM risk prediction model based on Meta-analysis has good predictive performance and can be used as a practical tool for T2DM risk prediction in middle-aged and elderly populations.