Search Results (78)

Erosion gullies can reduce arable land area and decrease agricultural machinery efficiency; therefore, automatic gully extraction on a regional scale should be one of the preconditions of gully control and land management. The purpose of this study is to compare the effects of the grey level co-occurrence matrix (GLCM) and topographic–hydrologic features on automatic gully extraction and guide future practices in adjacent regions. To accomplish this, GaoFen-2 (GF-2) satellite imagery and high-resolution digital elevation model (DEM) data were first collected. The GLCM and topographic–hydrologic features were generated, and then, a gully label dataset was built via visual interpretation. Second, the study area was divided into training, testing, and validation areas, and four practices using different feature combinations were conducted. The DeepLabV3+ and ResNet50 architectures were applied to train five models in each practice. Thirdly, the trainset gully intersection over union (IOU), test set gully IOU, receiver operating characteristic curve (ROC), area under the curve (AUC), user’s accuracy, producer’s accuracy, Kappa coefficient, and gully IOU in the validation area were used to assess the performance of the models in each practice. The results show that the validated gully IOU was 0.4299 (±0.0082) when only the red (R), green (G), blue (B), and near-infrared (NIR) bands were applied, and solely combining the topographic–hydrologic features with the RGB and NIR bands significantly improved the performance of the models, which boosted the validated gully IOU to 0.4796 (±0.0146). Nevertheless, solely combining GLCM features with RGB and NIR bands decreased the accuracy, which resulted in the lowest validated gully IOU of 0.3755 (±0.0229). Finally, by employing the full set of RGB and NIR bands, the GLCM and topographic–hydrologic features obtained a validated gully IOU of 0.4762 (±0.0163) and tended to show an equivalent improvement with the combination of topographic–hydrologic features and RGB and NIR bands. A preliminary explanation is that the GLCM captures the local textures of gullies and their backgrounds, and thus introduces ambiguity and noise into the convolutional neural network (CNN). Therefore, the GLCM tends to provide no benefit to automatic gully extraction with CNN-type algorithms, while topographic–hydrologic features, which are also original drivers of gullies, help determine the possible presence of water-origin gullies when optical bands fail to tell the difference between a gully and its confusing background. Full article

This study investigates the complex dynamics of new-type urbanization in resource-based county-level cities, using Wuan City in Hebei Province, China, as a representative case. As China pursues a high-quality development agenda, cities historically dependent on resource extraction face profound challenges in achieving sustainable and inclusive urban growth. This research employs a multi-method approach—including Theil index analysis, industrial shift-share analysis, a Cobb–Douglas production function model, and a composite urbanization index—to quantitatively diagnose the constraints on Wuan’s development and assess its transformation efforts. Our empirical results reveal a multifaceted situation: while the urban–rural income gap has narrowed, rural income streams remain fragile. The shift-share analysis indicates that although Wuan’s traditional industries have regained competitiveness, the city’s economic structure is still burdened by a persistent negative structural component, hindering diversification. Furthermore, the economy exhibits characteristics of a labor-intensive growth model with inefficient capital deployment. These underlying issues are reflected in a comprehensive urbanization index that, after a period of rapid growth, has recently stagnated, signaling the exhaustion of the city’s traditional development mode. In response, Wuan attempts an “industrial transformation-driven new-type urbanization” path. This study details the three core strategies being implemented: (1) incremental population urbanization through development at the urban fringe and in industrial zones; (2) in situ urbanization of the existing rural population; and (3) the cultivation of specialized “characteristic small towns” to create new, diversified economic nodes. The findings from Wuan offer critical, actionable lessons for other resource-dependent regions. The case demonstrates that successful urban transformation requires not only industrial upgrading but also integrated, spatially aware planning and robust institutional support. We conclude that while Wuan’s model provides a valuable reference, its strategies must be adapted to local contexts, emphasizing the universal importance of institutional innovation, human capital investment, and a people-centered approach to achieving resilient and high-quality urbanization. Full article

This study aims to mitigate slope-collapse hazards that threaten life and property at the Lujiawan resettlement site in Wanbi Town, Dayao County, Yunnan Province, within the Guanyinyan hydropower reservoir. It integrates centimeter-level point-cloud data collected by a DJI Matrice 350 RTK equipped with a Zenmuse L2 airborne LiDAR (Light Detection And Ranging) sensor with detailed structural-joint survey data. First, qualitative structural interpretation is conducted with stereographic projection. Next, safety factors are quantified using the limit-equilibrium method, establishing a dual qualitative–quantitative diagnostic framework. This framework delineates six hazardous rock zones (WY1–WY6), dominated by toppling and free-fall failure modes, and evaluates their stability under combined rainfall infiltration, seismic loading, and ambient conditions. Subsequently, six-degree-of-freedom Monte Carlo simulations incorporating realistic three-dimensional terrain and block geometry are performed in RAMMS::ROCKFALL (Rapid Mass Movements Simulation—Rockfall). The resulting spatial patterns of rockfall velocity, kinetic energy, and rebound height elucidate their evolution coupled with slope height, surface morphology, and block shape. Results show peak velocities ranging from 20 to 42 m s⁻¹ and maximum kinetic energies between 0.16 and 1.4 MJ. Most rockfall trajectories terminate within 0–80 m of the cliff base. All six identified hazardous rock masses pose varying levels of threat to residential structures at the slope foot, highlighting substantial spatial variability in hazard distribution. Drawing on the preceding diagnostic results and dynamic simulations, we recommend a three-tier “zonal defense with in situ energy dissipation” scheme: (i) install 500–2000 kJ flexible barriers along the crest and upper slope to rapidly attenuate rockfall energy; (ii) place guiding or deflection structures at mid-slope to steer blocks and dissipate momentum; and (iii) deploy high-capacity flexible nets combined with a catchment basin at the slope foot to intercept residual blocks. This staged arrangement maximizes energy attenuation and overall risk reduction. This study shows that integrating high-resolution 3D point clouds with rigid-body contact dynamics overcomes the spatial discontinuities of conventional surveys. The approach substantially improves the accuracy and efficiency of hazardous rock stability assessments and rockfall trajectory predictions, offering a quantifiable, reproducible mitigation framework for long slopes, large rock volumes, and densely fractured cliff faces. Full article

The gridded spatial distribution data of Gross Domestic Product (GDP) has a wide range of application values in many fields, such as regional economic analysis, urban planning, sustainable utilization of resources, and disaster risk assessment. However, currently the publicly accessible GDP grid datasets face limitations in terms of temporal coverage, spatial extent, and accuracy. Therefore, based on the remote sensing data of land use and nighttime light, this study developed two methods: the factor averaging method (FAM) and grid averaging method (GAM), and used Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) algorithms to jointly construct the spatial model of GDP, so as to produce China’s 1 km gridded GDP in 2020. The experimental results show the following: (1) The GAM yields higher R² values than the FAM in modeling the three industries, and therefore, it is adopted as the basis for GDP spatialization modeling. (2) XGBoost achieves higher R² values than RF in modeling primary and secondary industries, but lower R² values in modeling tertiary industry. Consequently, both methods are combined to construct the overall GDP spatialization model. (3) The accuracy of the GDP spatialization results is evaluated based on town-level GDP statistics, with an R² value of 0.78, indicating its reliable predictive capability. (4) Compared with publicly available GDP datasets, our dataset exhibits consistent spatial distribution patterns and aggregation trends. Furthermore, our GDP dataset provides a more detailed depiction of variations within county-level administrative units. Therefore, the method proposed in this study offers a valuable option for generating a gridded GDP dataset, visually displaying the uneven economic development across various regions in China. It helps to uncover economic disparities among regions and provides data support for formulating differentiated support policies, so as to promote balanced regional development among regions. Furthermore, it contributes to promoting sustained, inclusive, and sustainable economic growth (SDG 8) and reducing inequalities within and among countries (SDG 10), thereby providing strong support for urban planning and sustainable development. Full article

Scientific route selection is the premise of constructing the Grand Canal National Trails (GCNTs). How to highlight the historical and cultural characteristics of the cities along the Grand Canal and meet the diverse needs of urban residents and tourists through GCNTs while considering the reality is an important goal of the route selection research. Taking the old town of Jining City as an example, this study proposes a theoretical framework for route selection of the GCNTs based on resource connectivity, spatial continuity, and residents’ promotion, with a realization path of “three sections and six steps”. The results show that the optimal connection path between “canal–resource–community” can be found through systematic methods such as the optimized minimum cumulative resistance (MCR) model and space syntax, and the “main route–branch route–connection route” system of the GCNTs can be constructed. The GCNTs closely connect the canals, 59 resources, and 352 communities into an integral spatial network, forming a complete canal cultural narrative system and path. The results offer theoretical and methodological support for the route selection of GCNTs in 35 prefecture-level cities and 150 districts and counties along the Grand Canal, providing reference for route selections of similar related concepts in central urban areas. Full article

The vulnerability of Social–Ecological Systems (SES) is a frontier research topic in the field of geography. Research on drought vulnerability has emerged as a key area of focus in the study of SES vulnerability, and it has increasingly been recognized as a critical step in formulating policies for drought prevention and mitigation. In this study, the indicator system for drought vulnerability evaluation of SES in the Three-River Headwaters Region (TRHR) was established. This paper revealed the drought vulnerability evolution process and characteristics, and key driving indicators of SES at county-town-village spatial scales in six time periods of 1990, 2000, 2010, 2015, 2020, and 2023, and predicted the drought vulnerability of SES in 2050 under two scenarios. Results indicate that the average drought vulnerability in the TRHR decreased from 0.526 in 1990 to 0.444 in 2023. Compared to 1990, among the 82 selected towns, 85.37% experienced a decline in 2023, and among the 152 selected villages, 95.39% showed a reduction in 2023. Hot spots of drought vulnerability were concentrated in the southeast of the TRHR, while cold spots were in the northwest. From 1990 to 2000, the drought vulnerability of counties and towns in the TRHR increased, but it decreased between 2000 and 2023. In 1990, Henan County exhibited the highest drought vulnerability at the county level. Waeryi Town in Jiuzhi County had the highest vulnerability among towns, while Suojia Town in Zhidoi County had the lowest. Of the 152 selected villages, 41.45% exhibited relatively high or high levels of drought vulnerability, while 23.68% showed relatively low levels. In 2023, Jiuzhi County became the most vulnerable county, with Baiyu Town in Jiuzhi County ranking highest among towns and Suojia Town in Zhidoi County remaining the least vulnerable. At the village level, 22.37% exhibited relatively high or high vulnerability, whereas 42.11% showed relatively low or low levels. Drought disaster records, the proportion of agricultural and animal husbandry output value, the proportion of grassland, the proportion of large livestock, and the per capita disposable income surface are the key factors influencing drought vulnerability in the TRHR. By 2050, under the first scenario, the average drought vulnerability of the TRHR is projected to be 0.428, indicating a medium level, while the second scenario predicts a further reduction to 0.350, representing a relatively low level. The adaptive governance strategies to mitigate drought vulnerability in the TRHR include developing an integrated drought management system; establishing an ecological management, protection, and financial support model; and so on. Overall, this paper can provide scientific references and policy recommendations for policymakers and researchers on the aspects of drought vulnerability and sustainable development of SES. Full article

Background: Small-town residents face healthcare inequities that result in poorer outcomes compared to those living in urban areas. These disparities are deeply rooted in socioeconomic and demographic factors as well as in access to healthcare services. This study aimed to explore health disparities and community strengths within small towns in Williamson County, Central Texas, intensified by urban spillover. Methods: A qualitative study was designed using the Social Determinants of Health Model as the conceptual framework. We conducted eight in-depth interviews with local stakeholders. Each interview lasted 60–90 min and was audio-recorded, transcribed verbatim, and subjected to thematic analysis by trained researchers. Results: The participants reported that significant population growth, via individuals drawn from the rapidly expanding cities in proximity to their small towns, dramatically impacts lives. Eight main themes emerged: (1) low levels of community and professional health literacy and a lack of healthcare navigation support in schools and community-based support systems; (2) limited funding for healthcare services and limited capacity to support access to them; (3) limited access to food that can support healthy dietary patterns; (4) inadequate transportation services; (5) substance use, violence, and crime; (6) stressful community dynamics and an environment that negatively influences individual and community well-being; (7) financial instability and unreliable and insufficient infrastructure; and (8) community strengths and potential resources. Conclusions: Our findings reveal critical healthcare disparities in these small towns. Harnessing funding support and community unity is vital for developing equitable healthcare solutions and improving the well-being of residents in these rapidly evolving locales. Full article

Against the backdrop of intensifying global climate change, the impact of land use pattern changes on ecosystem vulnerability has garnered increasing attention. However, systematic studies concerning the ecological vulnerability of mountainous regions remains inadequate, with relevant policies primarily remaining at the macro-regulation level and lacking specific guidance measures. Taking Heishui County in southwest China as a case study, this research innovatively combines landscape pattern with the sensitivity–pressure–resilience (SPR) model to systematically analyze land use spatiotemporal evolution characteristics, ecological vulnerability and spatial differentiation patterns, and their driving mechanisms across multiple scales, including county, township, and land use types. The findings reveal that the region’s ecological vulnerability exhibits a spatial distribution pattern of “high in the southeast and low in the northwest”, with a radiating decrease from the centers of Longba and Weigu towns. The high degree of farmland landscape fragmentation is identified as a crucial factor contributing to its heightened ecological vulnerability. Geological disasters, human activities, meteorological conditions, and topographical features are the primary driving factors affecting ecological vulnerability intensity. Furthermore, land use pattern changes, characterized by landscape patch fragmentation, lack of dominant patch types, and decreased landscape diversity have further intensified regional ecological vulnerability. This research holds significant theoretical and practical implications for guiding ecological environmental governance in mountainous regions, enhancing ecological resilience, and promoting regional sustainable development. Full article

The planting of oat varieties is influenced by factors such as their inherent traits, ecological regional climate, altitude conditions, and resistance differences, resulting in a decrease in both forage yield and quality. It is crucial to carefully select appropriate oat varieties for different ecological regions in order to enhance forage yield and quality, thereby facilitating the advancement of the grass industry. The correlation between the indices and the relationship between the indices and varieties were investigated through rigorous correlation analysis and principal component analysis. By employing gray correlation analysis, the 21 indices were transformed into 15 independent comprehensive indices. Subsequently, based on a comprehensive analysis, oat varieties suitable for cultivation in different ecological regions were identified. In this study, fifteen domestic and foreign oat varieties were cultivated in the semi-arid region of Weiqi Town and the alpine region of Damaying Town in Shandan County throughout 2023. Among the yield traits, Everleaf 126 exhibited a significantly lower plant height while possessing the largest leaf area, the highest number of effective tillers, and achieving the highest hay and seed yields (p < 0.05), which were 13,199 kg/ha and 5136 kg/ha, respectively. The plant height of Longyan No.3 in Damaying Town was significantly higher than that of other varieties. This variety also demonstrated the highest number of effective tillers, along with the greatest hay yield (7783 kg/ha) and seed yield (5033 kg/ha). Among the evaluated quality traits, Everleaf 126 in Weiqi Town exhibited the highest leaf–stem ratio, crude protein content, and crude fat content (p < 0.05). In contrast, Mengshi in Damaying Town had the highest leaf–stem ratio, while Longyan No.3 demonstrated the highest levels of crude protein and crude fat content. Furthermore, Molasses displayed the highest soluble sugar content in both locations (p < 0.05). The resistance of 15 oat varieties to pests and diseases was found to be lower in Weiqi Town compared to Damaying Town. Notably, Everleaf 126 exhibited the highest resistance to powdery mildew, red leaf disease, leaf spot disease, and aphids among the varieties tested in Weiqi Town. In contrast, Longyan No.3 demonstrated superior resistance in Damaying Town. In conclusion, based on a comprehensive analysis of the gray correlation degree, in the semi-arid region, Everleaf 126 exhibited the most superior performance, followed by Molasses and Longyan No.3. In the alpine region, Longyan No.3 demonstrated the highest overall performance, followed closely by Molasses and Mengshi. These varieties exhibit significant potential for promotion as high-yield, high-quality forage oats in semi-arid and alpine environments. Full article

Forest management plans are the bibles of forest management. On the basis of these plans, farmers play essential roles in forest cultivation, protection, and utilization. After the forest tenure reform in the 2000s in China, the status of farmers has changed. For example, collective management has decreased and household management has become a leading structure of operation and management. Farmer’s dependence on income from forests has increased, which is reflected in their increased participation in management. However, insights into farmers’ perceptions of and willingness to participate in the formulation of forest management plans are insufficient. This study analyzes the factors influencing farmers’ participation by using an econometric model based on 1752 samples of farmer households from 10 counties. The empirical results reveal that according to farmers, forest type and property rights influence their willingness to participate in the formulation of forest management plans. In addition, whether there is a village leader, the village distance from town, the circulation of forest land, the area of woodland, timber price, and forestry income have a significant positive impact on farmers’ willingness to participate in forest management plan formulation; the level of education and non-agricultural income have a significant negative impact on farmers’ willingness to participate in forest management program development. Finally, this study proposes to improve and deepen the reform of the forest ownership system, encourage land circulation, and give play to the role of village leaders in promoting the participation of farmers in forest management plans, so as to improve the efficiency of forest management. Full article

Over the past decades, China has experienced severe compound natural disasters, such as extreme rainfalls, which have led to significant losses. In response to the challenges posed by the lack of a clear investigation process and inadequate comprehensiveness in evaluating the natural disaster chains, this study proposes a comprehensive retrospective simulation strategy for emergency investigation and simulation of heavy rainstorm–flash flood–debris flow chain disasters at the county–town level. The primary aim is to avert potential new chain disasters and alleviate subsequent disasters. This study combines emergency investigation efforts with hydrodynamic models to digitally simulate and analyze compound chain disasters triggered by an extreme rainfall event in the Haihe River regional area, specifically Gaoyakou Valley, Liucun Town, Changping District, Beijing, in July 2023, along with potential new disasters in adjacent regions. The findings indicate that the heavy rainstorm chain disaster on “7.29” resulted from a complex interplay of interrelated natural phenomena, including flash floods, debris flows, urban floodings, and river overflows. Hantai Village has experienced flash flood and debris flow events at different times in this area. Should the rainfall volume experienced in Liucun Town be replicated in the Ming Tombs Town area, approximately 6.2 km² of land would be inundated, leading to damages to 458 residences and impacting around 240 ha of agricultural land. The anticipated release of floodwater from the reservoir would lead to significant impacts on downstream residents and roads. Our research can improve the efficacy of emergency investigations and assessments, which in turn can help with the management and reduction of disaster risks at the grassroots level. Full article

Studies on urban shrinkage in eastern China lack relevant contributions. This study investigates population dynamics in Jiangsu Province, focusing on county-level cities to understand the factors influencing urban population size. It developed a multidimensional indicator system per 2014, 2017, 2020, and 2023 statistical data, incorporating road network accessibility, socio-economic levels, resident income, public services, and the built environment. Employing static fixed effects models and dynamic panel regression models, it analyses trends and evolutionary patterns of permanent population changes. The findings indicate an overall increase in the permanent population over the past decade, although the growth rate has slowed in the last five years. Notably, there is a significant spatial clustering of population growth and contraction, often aligned with high-speed transportation corridors. Unlike existing research findings, the urban shrinkage pattern in Jiangsu Province is unique. Some cities in northern Jiangsu exhibit a ‘relative contraction’ pattern, where population decline coexists with high economic growth and spatial expansion. Key short-term factors influencing population size include the city’s economic level and residents’ disposable income, while long-term factors encompass city level, industrial structure, and transportation networks. Small towns exhibit ‘close-range mobility’, with primary short-term influences stemming from residents’ income, public service quality, and intercity transportation accessibility. Indeed, long-term factors primarily reflect economic development quality and urban employment rates. Full article

Indoor air quality (IAQ) poses a significant public health concern, and exposures to high levels of fine particulate matter (PM_2.5) and carbon dioxide (CO₂) could have detrimental health impacts. This study focused on assessing the indoor air pollutants in a residential house located in the town of Mission, Hidalgo County, South Texas, USA. The PM_2.5 and CO₂ were monitored indoors: the kitchen and the bedroom. This investigation also aimed to elucidate the effects of household activities such as cooking and human occupancy on these pollutants. Low-cost sensors (LCSs) from TSI AirAssure™ were used in this study. They were deployed within the breathing zone at approximately 1.5 m above the ground. Calibration of the low-cost sensors against Federal Equivalent Method (FEM) instruments was undertaken using a multiple linear regression method (MLR) model to improve the data accuracy. The indoor PM_2.5 levels were significantly influenced by cooking activities, with the peak PM_2.5 concentrations reaching up to 118.45 μg/m³. The CO₂ levels in the bedroom increased during the occupant’s sleeping period, reaching as high as 1149.73 ppm. The health risk assessment was assessed through toxicity potential (TP) calculations for the PM_2.5 concentrations. TP values of 0.21 and 0.20 were obtained in the kitchen and bedroom, respectively. The TP values were below the health hazard threshold (i.e., TP < 1). These low TP values could be attributed to the use of electric stoves and efficient ventilation systems. This research highlights the effectiveness of low-cost sensors for continuous IAQ monitoring and helps promote better awareness of and necessary interventions for salubrious indoor microenvironments. Full article

In urban areas, water is usually provided through piped systems from specific sources to consumers. Cities, towns, and peri-urban settlements typically benefit from piped systems, while rural areas rely on water supplies from surface sources like rivers and canals, as well as ground sources such as wells and tube wells. When traditional methods fail, alternative water supply systems emerge in both urban and rural areas. This paper addresses the question of whether alternative water supply arrangements are sustainable in terms of system reliability, consumer acceptance, cost-effectiveness, convenience, perceptions of service levels, and ease of access to service providers. This paper examines the status of alternative water supply arrangements in Turkana County, Kenya, and Orangi in Karachi, Pakistan, using qualitative methods. It highlights that underprivileged communities commonly turn to alternative water supply arrangements when conventional methods are unavailable or underperforming. Full article

The WuShen counties in the hinterland of the Maowusu Sandland are located in the “ecological stress zone” of the forest–steppe desert, with low vegetation cover, a strong ecosystem sensitivity, and poor stability under the influence of human activities. Therefore, it is important to study and analyze the changes in vegetation growth in this region for the purpose of objectively evaluating the effectiveness of desertification control in China’s agricultural and pastoral intertwined zones, and formulating corresponding measures in a timely manner. In this paper, the spatial and temporal variations in the vegetation NDVI in the WuShen counties of the Maowusu Sandland and their response relationships with driving factors were investigated by using a trend test, center of gravity transfer model, partial correlation calculation, and residual analysis, and by using the MOD13A3 vegetation NDVI time series data from 2000 to 2020, as well as the precipitation, temperature, and potential evapotranspiration data from the same period. The results showed the following: ① The regional vegetation NDVI did not fluctuate significantly with latitude and longitude, and the NDVI varied between 0.227 and 0.375 over the 21-year period, with a mean increase of 0.13 for the region as a whole and an increase of 0.61 for the region of greatest change. Of the area, 86.83% experienced a highly significant increase, and the trend in increase around rivers and towns was higher than that in the northwestern inland flow area, with the overall performance of “low in the west and high in the east”. ② Only 2.07% of the vegetation NDVI center of gravity did not shift, and the response with climate factors was mainly characterized by having consistent or opposite center of gravity changes with precipitation and potential evapotranspiration. ③ Human activities have been the dominant factor in the vegetation NDVI change, with 75.89 percent of the area positively impacted by human activities, and human activities in the southwest inhibiting the improvement of vegetation in the area. The impact of human activities on the unchanged land type area is increasing, most obviously in the farmland area, and the impact of human activities on the changed land type area is gradually decreasing in the area where the farmland becomes impervious. The vegetation in the area above 1300 m above sea level is degraded by the environment and human activities. The research results can provide scientific support for the implementation of ecological fine management and the formulation of corresponding ecological restoration and desertification control measures in the Maowusu Sandland. At the same time, it is expected to serve as a baseline for other studies on the evolution of vegetation in agro-pastoral zones. Full article