Search Results (1,348)

The plain river network region is faced with ecological and environmental challenges such as insufficient hydrological connectivity and degradation of ecosystem services under the influence of urbanization and human activities, and therefore attention needs to be paid to river network changes in this region and the synergistic benefits of natural–social–economic multidimensional factors. This study took the Lixiahe region, a typical plain river network region, as the research object, using Mann–Kendall, spatial autocorrelation analysis, random forest, multiple validation and Granger causality test of key drivers to analyze the spatiotemporal evolution of its river network from 2013 to 2025 and quantify driving mechanisms from natural, social and economic factors. The results showed that: (1) From 2013 to 2025, the Lixiahe Plain river network region tended to be trunk and artificial, with the number and connectivity of river networks showing an upward trend while the curvature of river network decreased significantly. (2) The Global Moran’s I index of the Lixiahe Plain river network decreased from 0.612 to 0.534, indicating a continued weakening of spatial agglomeration in the water area and exhibiting characteristics of edge fragmentation. (3) Random forest analysis showed that socioeconomic factors dominated recent river network change in the Lixiahe Plain. Economic factors mainly influenced quantity-related indicators, while social factors were more important for meander degree and connectivity in several ecologically sensitive counties. Multilevel validation demonstrated the robustness and generalization ability of the model. Granger causality analysis further indicated that GDP, road network density, freshwater aquaculture area, and agricultural output statistically preceded changes in key hydrological indicators. These findings suggest that river network management in plain river network regions should move beyond quantity-based engineering expansion and adopt a multi-indicator, spatially differentiated approach. Integrating river quantity, morphology, and connectivity into management can better support the balance between socioeconomic development and ecological protection and promote the sustainable optimization of river network. Full article

The dynamic interplay between urban polycentric structure and habitat quality profoundly shapes the pathways and outcomes of urban sustainable development. Based on the nighttime light index and economic aggregate data of 289 county-level units in the Yangtze River Delta region (2008–2023), this study identifies a polycentric urban structure and measures the polycentricity index of 41 prefecture-level cities. An ecological environment quality evaluation index system is constructed to analyze their influencing factors, followed by an exploration of the trade-off and synergy relationship between the two systems. The main findings are: (1) Both the nighttime light-based urban structure index and economic aggregate index exhibited a circularly decreasing pattern centered on Shanghai. (2) The “nighttime light–economic aggregate” polycentricity index showed a significant spatial “point–core” distribution, with gradually expanding outward diffusion over time. (3) The ecological environment quality achieved significant overall improvement, with better conditions in the southeast than the northwest. (4) Pearson correlation analysis confirms a significant positive correlation between a polycentric urban structure and ecological environment quality; the relationship is categorized into four types: strong trade-off, weak trade-off, weak synergy, and strong synergy. This study provides solid theoretical support and scientific decision-making guidance for urban future development planning and ecological protection practices. Full article

The Digital Elevation Model (DEM), a crucial data source for waterlogging simulations, significantly influences the accuracy of the results. In complex urban environments, low-resolution DEMs cannot accurately capture the depressional characteristics of city roads or water levels during river floods, leading to distorted urban flooding simulations. To this end, this study developed a novel technique to refine the public 30 m resolution DEM to 1 m resolution for the urban area. The method establishes a zero-flood-depth baseline by correcting the elevations of key elements to improve the accuracy of urban inundation simulations. This is achieved through a semi-automated vector–raster integration workflow, which includes (1) road elevation correction that classifies road vectors, samples elevation at end points, and applies linear interpolation to depict roads as depressions and (2) waterway elevation correction that raises riverbed levels to match adjacent banks, simulating a pre-flood critical state. Polk County in Florida, USA, and the Central Business District (CBD) in Beijing, China, were selected as the research areas. In Polk County, we directly verified its accuracy using the official 1m LiDAR DEM. The results show that the mean error (ME), the root mean square error (RMSE), and the Standard Deviation (SD) improved by approximately 9%, 20%, and 65%, respectively, compared with previous methods. In Beijing, we used a volume matching algorithm to simulate urban flood depths under different rainfall scenarios, indirectly validating the results by comparing the simulated inundation volumes with the theoretical rainfall amounts. The refinement of the DEM significantly improved the topological accuracy of the river channels and the reliability of flood depths, and we analyzed two types of water accumulation behavior patterns. Overall, this study innovatively integrates public raster and vector data, utilizing known attribute information to refine public datasets and construct a highly precise water accumulation model. Full article

Global urbanization has long been hampered by the “metrocentric priority” paradigm, with small towns—core hubs for urban–rural integration—severely undervalued in practical value. Amid China’s transition to high-quality urban–rural integration, unbalanced small town development has become a critical bottleneck for county-level factor flows, demanding systematic research to unlock their strategic value and resolve urban–rural dual predicaments. Existing studies suffer from scientific gaps including unidirectional linear cognition, insufficient complex system thinking, and weak interpretation of regional heterogeneity, remaining at the stage of static correlation description and failing to reveal the two-way reciprocal feedback logic between small towns and urban–rural integration. Meanwhile, the application of complex system theory in urban–rural research is still confined to theoretical narratives, which hinders the advancement of research from descriptive analysis to mechanism interpretation. Taking Henan Province (a typical agricultural and populous province reflecting China’s urban–rural development) as a case, this study builds a “local emergence–global synergy” framework based on complex system theory, establishes a dual indicator system for small towns’ multidimensional performance and county-level urban–rural integration, and integrates spatial statistical analysis, bidirectional regression and coupling coordination models to explore their cross-scale spatiotemporal evolution and reciprocal feedback during 2019–2023. Findings show the following: (1) The multidimensional performance of small towns presents a pattern characterized by polarized expansion of high-value regions and overall improvement of low-value regions, while county-level urban–rural integration evolves into a polycentric structure featured by central dominance and southern growth. (2) There is a significant two-way asymmetric relationship between small towns’ multidimensional performance and county-level urban–rural integration: the positive effect is significantly stronger than the reverse effect, and both direct impacts are significantly weakened after introducing economic variables, indicating that economic development serves as a key transmission channel. (3) The coupling mechanism presents three evolutionary paths with pronounced core–periphery spatial heterogeneity. Grounded in complex system theory, this study constructs a systemic analytical framework of “local emergence of small-town subsystems and global synergy of county-level systems”, verifies the core proposition of two-way interactions between subsystems and the overall system in the urban–rural complex giant system, and enriches the localized application of complex system theory and the urban–rural continuum theory in traditional agricultural regions of China. This study provides a foundational empirical paradigm for the in-depth exploration of nonlinear characteristics and threshold effects in future research. It offers theoretical support for policy formulation of county-level urban–rural integration in traditional agricultural regions of China, and it provides Chinese experiences for the Global South with similar contexts to explore inclusive urbanization pathways, promoting cross-cultural dialogue and practical transformation of urban–rural integration theory. Full article

Tick-borne diseases are an increasing public health concern in Europe, driven by climate change, landscape transformation, and expanding human activity. Urban green spaces provide suitable habitats for ticks and increase human exposure to tick-borne pathogens (TBPs), yet habitat-specific patterns in urban and suburban environments remain poorly characterized. This study examined tick distribution and TBPs prevalence across 11 urban and suburban sites in Kaunas County, Lithuania. A total of 1539 questing Ixodes ricinus ticks were collected and screened by real-time PCR for Borrelia spp., Anaplasma phagocytophilum, Neoehrlichia mikurensis, Rickettsia spp., and Babesia spp., with further species identification by sequencing. Borrelia spp. were most prevalent (24.43%), followed by Rickettsia spp. (7.60%), N. mikurensis (6.63%), A. phagocytophilum (3.64%), and Babesia spp. (2.53%). Tick density, pathogen prevalence, and species diversity varied among habitats, with higher values in forested and ecotonal areas, but notable infection rates were also observed in managed urban sites. Co-infections occurred in 18.8% of infected ticks. Our findings demonstrate that the circulation of TBPs in urban and suburban landscapes is shaped by local habitat features, host communities, and management intensity, highlighting the need for habitat-specific risk assessment in urban planning and public health. Full article

Background/Objective: Health is a multidimensional construct shaped not only by clinical conditions but also by psychological, social, environmental and cultural factors. In low- and middle-income countries undergoing rapid epidemiological transition, understanding health requires integrated and culturally informed approaches. However, quality of life, perceived health status and lifestyle behaviors are often investigated separately, limiting the interpretation of well-being in specific local contexts. This study aimed to provide an integrated assessment of quality of life, perceived health status and lifestyle behaviours among adults attending a peri-urban public hospital in Kenya, using internationally validated instruments applied within a specific local cultural context. Methods: A cross-sectional observational study was conducted at Tigoni Level 4 Hospital, Kiambu County, Kenya. Adult outpatients (N = 40) were consecutively recruited. Quality of life was assessed using the WHOQOL-BREF, perceived health status using the EQ-5D-5L and EQ-VAS, and lifestyle behaviours using selected modules of the WHO STEPS instrument. Descriptive statistics were performed, and exploratory associations were examined using Spearman’s rank correlation coefficient. Results: Participants had a mean age of 35.9 ± 11.4 years, with a balanced gender distribution. Lifestyle risk factors were prevalent, including insufficient physical activity (40%) and overweight or obesity (>50%). WHOQOL-BREF scores revealed a heterogeneous profile, with relatively preserved social relationships and lower scores in the psychological and environmental domains. Pain/discomfort and anxiety/depression were the most frequently reported EQ-5D-5L problems. The mean EQ-VAS score was 68.2 ± 15.7. Perceived health was positively associated with physical and psychological quality of life, while higher body mass index was associated with lower physical quality of life. Mental health emerged as a cross-cutting factor across instruments. Conclusions: The findings highlight the multidimensional nature of health in a peri-urban Kenyan context and suggest the importance of considering local social and cultural influences when interpreting standardized health measures. Mental health and environmental conditions play a central role in shaping quality of life and perceived health, while lifestyle risk factors are already prevalent in a relatively young outpatient population. Integrating standardized health measures within a cross-cultural framework may support more holistic and person-centred approaches in primary care and public health in similar settings. Full article

Using She County, a national new-type urbanization comprehensive pilot area, as a case study, this research develops a multi-layered “static–dynamic–driver” analytical framework based on rural settlement data. By integrating GIS spatial overlay, landscape pattern indices, average nearest neighbor analysis, kernel density estimation, and cold–hotspot analysis, the study systematically characterizes the spatiotemporal evolution and driving mechanisms of rural settlements from 1980 to 2020. The results reveal that: (1) settlement evolution exhibits distinct phase-specific patterns, encompassing four primary types of transformation: localized expansion and consolidation, individual disappearance, rapid expansion, and the emergence of new settlements with peripheral extension; (2) landscape pattern and aggregation analyses indicate continuous growth in both total area and number of settlements, accompanied by increasing irregularity and fragmentation of patches; settlement size aggregation shows a fluctuating decline followed by recovery, overall spatial clustering intensity trends upward, and high-density kernel areas shift from the central–western to the northwestern region; (3) under multi-factor interactions, settlement layouts transitioned from an early “survival–location dependent” pattern dominated by natural constraints and transportation accessibility, to a mid-stage rapid aggregation driven by economic development and public service provision, ultimately evolving into a composite pattern balancing economic drivers and ecological constraints. The findings underscore the nonlinear superimposed effects of natural environment, economic development, transportation accessibility, public service availability, and ecological carrying capacity, providing a robust scientific basis for optimizing rural settlement spatial arrangements and informing rural development policy under the context of national new-type urbanization. Full article

Understanding vegetation-mediated mitigation of urban heat islands (UHI) is essential for sustainable urban adaptation strategies. Although vegetation responses to extreme heat events have been widely explored using satellite remote sensing and statistical methods, evidence remains limited regarding how these responses vary along urban–rural gradients, particularly in terms of resistance and recovery dynamics. This study focuses on the North Tianshan Slope Urban Agglomeration (TNSUA) in Xinjiang, China. Based on Enhanced Vegetation Index (EVI) data from 2000 to 2022, an urban–rural gradient was delineated using impervious surface fraction. Vegetation resistance and recovery during extreme heat events were quantified to reveal spatiotemporal response patterns. Generalized additive models (GAMs) and Random Forest (RF) models were applied to identify key driving factors and to evaluate their relative importance across multiple spatial scales. The results indicate that rural land cover along the gradient provides a strong cooling effect, particularly in areas with an urban development intensity (UDI) of 70–85%. Vegetation responses show pronounced seasonal differences, with urban vegetation generally exhibiting lower resistance and recovery than rural vegetation. At the county scale, local UHI intensity is the dominant driver of vegetation responses, whereas at the pixel scale, precipitation and vapor pressure deficit (VPD) play the most critical roles. Overall, this study improves the understanding of vegetation responses to extreme heat events in arid regions and provides scientific support for nature-based urban heat adaptation strategies. Full article

We use Reiterative Truncated Projected Least Squares (RTPLS) to estimate the correlation between real GDP per capita and income inequality for the 159 counties in Georgia, USA, from 2011 to 2021. RTPLS produces a separate slope estimate for every observation (data point), where differences in these slope estimates are due to omitted variables. Our measure of inequality is the ratio of household income at the 80th percentile divided by income at the 20th percentile. We find that the negative marginal correlation between income inequality and real per capita income has strengthened over time, and there are large differences between the effects for different counties. For example, in 2021, our estimate for d(real per capita GDP)/d(income inequality) ranged from −3.70 to −28.48. We find that this estimate becomes more negative when there are increases in the percentage of the county population with some college education, the percentage of the county population that is Black, the percentage of the county population that is Hispanic, as well as when unemployment increases. However, d(real percapita GDP)/d(income inequality) becomes less negative as the percentage of the county that is rural increases and as the percentage of the population that is less than 18 years old increases. Full article

The mountainous regions of southwest China represent one of the world’s most distinctive and sensitive areas. Against the backdrop of rapid urbanization and water conservancy construction, rural landscapes in these regions face challenges such as fragmentation, homogenization, and loss of local distinctiveness. Responding to the initiative of the European Landscape Convention (ELC), this study takes the Longchuan River Basin in Southwest China as a case study, and constructs a rural Landscape Character Assessment (LCA) framework adapted to the multi-level governance system. We established a multi-scale evaluation system covering large scale (county-level), medium scale (township-level), and detailed scale (reservoir area-level). The large scale integrated 6 categories of natural variables, while the medium scale involved 4 categories of natural variables and 4 categories of cultural variables. Using a Principal Component Analysis–Two-Step Clustering coupled method and eCognition software, landscape character types and areas were identified respectively. The results show that 11 landscape character types and 41 landscape character areas were identified at the large scale, and 6 landscape character types and 73 landscape character areas at the medium scale. At the detailed scale, 4 typical reservoir areas were selected for field surveys, which verified the in-depth impact of hydropower construction on landscape characteristics. The study provides a transferable technical pathway and policy recommendations for monitoring and managing rural landscapes in mountainous regions. Supports the long-term sustainability and resilience of rural landscapes in China. Full article

Given less than five years remaining until the target year for the first phase of China’s dual carbon goals, this paper studies carbon allowance allocation with an in-depth study of Jiangsu Province due to its significant role in driving the Yangtze River Delta’s pioneering achievement of the dual carbon goals. This study considered 2017 (the intermediate target year) as the base year and incorporated socio-economic data such as population, GDP, and the urbanization rate. Then, methods including the entropy weight method, gravity model and social network analysis were applied to classify Jiangsu’s 95 counties. From a regional coordination perspective, carbon governance clusters were constructed with the Shapley value, based on which spatial heterogeneity patterns were analyzed, and a carbon quota allocation was proposed. The findings reveal that: (1) The dominant factors influencing cross-scale carbon reduction capacity at the county level are natural carbon sink capacity (indicator weight: 0.180) and urbanization rate (indicator weight: 0.145). (2) The correlation between carbon reduction factors among different districts and counties exhibits an uneven spatial pattern. And the spatial configuration exhibits a multi-tiered, network-like distribution. (3) Through conducting spatial analysis and spatial grouping, Jiangsu could be divided into 14 county-level carbon governance alliances, with the number of member counties ranging from 4 to 10 within each alliance. (4) The allocation of carbon quotas in Jiangsu exhibits a distinct descending gradient from the southern to the northern regions, which is coupled with the regional economic geography. This is exemplified by the highest quota in Jiangyin (496.46 Mt) in the south and the lowest in Lianyun (34.90 Mt) in the north. It is concluded that two carbon emission reduction pathways should be established as a priority: (a) Tongshan-Gulou (Xuzhou)-Yunlong-Quanshan-Jiawang and (b) Tianning-Jiangyin-Zhangjiagang-Changshu-Taicang-Kunshan. Full article

This study systematically analyzes the spatio-temporal evolution, trade-offs, synergies and driving mechanisms of five ecosystem services (ESs) in Fujian Province (carbon storage, CS; habitat quality, HQ; sediment delivery ratio, SDR; water yield, WY; food provision, FP) based on multi-source data from 2003, 2013 and 2023 by adopting the InVEST model, Spearman correlation analysis, geographically weighted regression (GWR), self-organizing maps (SOM) and geographic detectors. Results show that: (1) ESs present a spatial pattern of “high in northwest and low in southeast” in Fujian; CS, HQ and FP show an overall decline, while SDR and WY increase significantly. (2) ES trade-offs and synergies have obvious scale effects and spatial heterogeneity, with stronger relationship intensity at the county level than the grid level, and FP generally shows a trade-off relationship with other services. (3) Land use is the key driving factor for CS, FP and HQ; precipitation dominates the changes in WY and SDR; and dual-factor interactions generally enhance the explanatory power of ES changes. The findings enrich the theoretical system of multi-scale ES trade-off and synergy research under rapid urbanization and provide a scientific basis for sustainable territorial spatial planning and differentiated ecological governance in Fujian. Meanwhile, the research framework can serve as a reference for ES management in other coastal mountainous regions worldwide, contributing to the realization of regional sustainable development goals (SDGs). Full article

Rapid urbanization has transformed the face of Texas by converting agricultural and natural lands into expanding built-up areas. This study analyzes and simulates land-use and land-cover (LULC) changes in Kaufman County, Texas, one of the fastest-growing counties in the United States, using a hybrid Cellular Automata–Artificial Neural Network (CA–ANN) model within the Quantum Geographic Information System (QGIS) Modules for Land-Use Change Evaluation (MOLUSCE) framework. Multitemporal NLCD datasets (2001, 2011, and 2021) and six spatial drivers: Elevation, Slope, Aspect, Distance from Roads and Rivers, and Built-up Density were used in the modeling framework. Transition relationships were calibrated using the 2001–2011 LULC data, and the model was validated by simulating the 2021 LULC map from the 2011 baseline. The calibrated model was then used to simulate future LULC scenarios for 2031, 2041, and 2051. Model validation yielded an overall Kappa value of 0.84 and a correctness of 90.9%, indicating high similarity between the observed and simulated maps. The results indicate simulated urban expansion, with built-up areas increasing by nearly 30% by 2051 at the expense of cropland and open areas, with forest and water bodies slightly increasing, and wetlands remaining stagnant. The CA–ANN model effectively captured the nonlinear, spatially dependent land-transition patterns using open-source tools. These findings provided useful information for sustainable land-use planning and environmental management, with the potential to incorporate spatial modeling into regional development strategies in rapidly urbanizing areas of Texas. Full article

Serving as a link between cities and villages, small towns play a crucial role in reducing the disparity between urban and rural areas. The spaces of small towns in Southern Jiangsu Province not only showcase the landscape style of production–living–ecological but also embody local cultural characteristics, acting as a unique “container” for preserving the memory of Jiangnan water towns. However, during the urbanization process, these spaces often fail to respect the principles of landscape locality, instead favoring standardization and efficient designs that overlook human perspectives on landscape perception and understanding. This results in the “homogenization” and “heterogenization” of Jiangnan small towns landscape spaces. As county urbanization shifts toward improving human environments, human-scale spatial perception has become key to localized planning. By combining street view photos with deep learning, the ‘2bulu’ dataset supports large-scale analysis of crowd perception and precise detection of spatial and landscape features. This study investigated the proportions of landscape elements in the small towns’ town–rural–wilderness of Wujiang District that play a direct role in shaping people’s perceived visual identity and sense of cultural resonance, assessed the spatial distribution of perceived landscape locality scores, and revealed the positive or negative correlations between the proportions of visual landscape elements and the sense of place. This study analyzed perceived landscape locality in Wujiang small towns based on crowd perception, exploring which town–rural–wilderness landscape elements are perceived as having local character, and highlighted the importance of preserving locality through integrated town–rural–wilderness landscape elements. The findings offer insights for quantitative measuring landscape locality perception and support planning of appropriate local landscapes in Jiangnan small towns. Full article

Background: Severe fever with thrombocytopenia syndrome (SFTS) has become an increasing public health threat in China, with Yantai City representing a major endemic focus. A fine-scale, long-term epidemiological analysis integrating human case data with vector surveillance is essential for understanding local transmission dynamics. Methods: We conducted a retrospective analysis using 12-year (2013–2024) county-level SFTS surveillance data from Yantai City. Temporal trends were analyzed by Joinpoint regression. Concurrent field surveillance of Haemaphysalis longicornis (2019–2024) was used to quantify local SFTSV infection rates in ticks. Associations between SFTS incidence and environmental/livestock factors were evaluated using Spearman’s correlation and multivariable negative binomial regression. Results: A total of 1964 SFTS cases were reported. The annual incidence rate increased from 0.65 to 5.12 per 100,000 population, with an average annual percentage change (AAPC) of 13.56% 2013–2024, showing the most substantial rise among the elderly. Marked spatial heterogeneity was observed, with county-level mean incidence ranging from 0.30 to 5.23 per 100,000. The SFTSV infection rate in ticks surged from 0.54% in 2019 to 3.24% in 2024, and showed a strong positive correlation with human incidence both seasonally (ρ = 0.998) and across counties (ρ = 0.79), a pattern likely driven by shared environmental factors. Multivariable analysis identified grassland coverage (adjusted IRR [aIRR] = 1.21), woodland coverage (aIRR = 2.31), goat density (aIRR = 1.49), and tick infection rate (aIRR = 1.65) as independent risk factors, while urban land was protective (aIRR = 0.83). The overall case fatality rate was 8.86%, showing a declining trend, but was significantly higher in males (10.90%) than in females (7.04%), particularly among the elderly. Conclusions: SFTS incidence in Yantai increased significantly over the past decade, characterized by a heightened burden on the elderly and strong spatiotemporal clustering. Risk is independently mediated by ecological interfaces, notably woodland/grassland habitats and goat rearing. These findings delineate high-risk areas and populations, offering crucial insights for developing targeted public health strategies. Full article