Search Results (108)

To study the generation and dissipation process of agglomerate fog in mountainous expressways and deeply understand the hazard mechanisms of agglomerate fog sections in mountainous expressways, based on the analysis of the geographical location characteristics of mountainous expressways and the spatial and temporal distribution characteristics of agglomerate fog, the airspace constitutive model of agglomerate fog in mountainous expressways was constructed based on Newton constitutive theory. Firstly, the properties of the Newtonian fluid and cluster fog were compared and analyzed, and the influence mechanism of environmental factors such as the altitude difference, topography, water system, valley effect, and vegetation on the generation and dissipation of agglomerate fog in mountainous expressways was analyzed. Based on Newton’s constitutive theory, the constitutive model of temperature, humidity, wind speed, and agglomerate fog points in the foggy airspace of the mountainous expressway was established. Then, the time and spatial distribution of fog in Chongqing and Guizhou from 2021 to 2023 were analyzed. Finally, the model was verified by using the meteorological data and fog warning data of Liupanshui City, Guizhou Province in 2023. The results show that the foggy airspace of mountainous expressways can be defined as “the space occupied by the agglomerate fog that occurs above the mountain expressway”; The temporal and spatial distribution of foggy airspace on expressways in mountainous areas is closely related to the topography, water system, vegetation distribution, and local microclimate formed by thermal radiation. The horizontal and vertical movements of the atmosphere have little influence on the foggy airspace on expressways in mountainous areas. The specific manifestation of time distribution is that the occurrence of agglomerate fog is concentrated from November to April of the following year, and the daily occurrence time is mainly concentrated between 4:00–8:00 and 18:00–22:00. The calculation results of the foggy airspace constitutive model of the expressway in the mountainous area show that when there is low surface radiation or no surface radiation, the fogging value range is [90, 100], and the fogging value range is [50, 70] when there is high surface radiation (>200), and there is generally no fog in other intervals. The research results can provide a theoretical basis for traffic safety management and control of mountainous expressway fog sections. Full article

While significant progress has been made in controlling point source pollution, agricultural non-point source pollution (AGNPSP) has emerged as a major contributor to global water pollution, posing a severe threat to ecological quality. According to China’s Second National Pollution Source Census, AGNPSP constitutes a substantial proportion of water pollution, making its mitigation a critical challenge. Identifying AGNPSP risk zones is essential for targeted management and effective intervention. This study focuses on Yongchuan District, a representative hilly–mountainous area in the Yangtze River Basin. Applying the landscape ecology “source–sink” theory, we selected seven natural factors influencing AGNPSP and constructed a minimum cumulative resistance model using remote sensing post-processing data. An attempt was made to classify the “source” and “sink” landscapes, and ultimately conduct a risk assessment of AGNPSP in Yongchuan District, identifying the key areas for AGNPSP control. Key findings include: 1. Vegetation coverage is the most significant natural factor affecting AGNPSP. 2. Extremely high- and high-risk zones cover 90% of Yongchuan, primarily concentrated in the central and southern regions, indicating severe AGNPSP pressure that demands urgent management. 3. The levels of ammonia nitrogen and total phosphorus in the typical sections are related to the risk levels of the corresponding sections. Consequently, the risk level of AGNPSP directly correlates with the pollutant concentrations measured in the sections. This study provides a robust scientific basis for AGNPSP risk assessment and targeted control strategies, offering valuable insights for pollution management in Yongchuan and similar regions. Full article

This study used Jilin-1 satellite data and unmanned aerial vehicle (UAV)-collected visible-thermal infrared imagery to calculate twelve spectral indices and evaluate their effectiveness in distinguishing post-fire forest areas and identifying human-altered land-cover changes in Jinyun Mountain, Chongqing. The research goals included mapping wildfire impacts with M-statistic separability, measuring land-cover distinguishability through Jeffries–Matusita (JM) distance analysis, classifying land-cover types using the random forest (RF) algorithm, and verifying classification accuracy. Cumulative human disturbances—such as land clearing, replanting, and road construction—significantly blocked the natural recovery of burn scars, and during long-term human-assisted recovery periods over one year, the Red Green Blue Index (RGBI), Green Leaf Index (GLI), and Excess Green Index (EXG) showed high classification accuracy for six land-cover types: road, bare soil, deadwood, bamboo, broadleaf, and grass. Key accuracy measures showed producer accuracy (PA) > 0.8, user accuracy (UA) > 0.8, overall accuracy (OA) > 90%, and a kappa coefficient > 0.85. Validation results confirmed that visible-spectrum indices are good at distinguishing photosynthetic vegetation, thermal bands help identify artificial surfaces, and combined thermal-visible indices solve spectral confusion in deadwood recognition. Spectral indices provide high-precision quantitative evidence for monitoring post-fire land-cover changes, especially under human intervention, thus offering important data support for time-based modeling of post-fire forest recovery and improvement of ecological restoration plans. Full article

Rural tourism plays a crucial role in promoting industrial revitalization in mountainous regions. Drawing inspiration from the site selection mechanisms of nature reserves, this study constructs a gap analysis framework tailored to rural tourism destinations, aiming to provide technical support for their spatial layout and systematic planning. By integrating a potential evaluation system based on tourism resources, market demand, and synergistic factors, the study identifies rural tourism priority zones and proposes a development typology and spatial optimization strategy across five provinces in Southwest China. The findings reveal: (1) First- and second-priority zones are primarily located in the core and periphery of provincial capitals and prefecture-level cities, while third-priority zones are concentrated in resource-rich areas of Yunnan and Guizhou and market-oriented areas of Sichuan, Chongqing, and Guangxi. (2) The Chengdu Plain emerges as the core region for rural tourism development, with hotspots clustered around Chengdu, northern and western Guizhou, central Chongqing, eastern Guangxi, and northwestern Yunnan, whereas cold spots are mainly situated in the western Sichuan Plateau and the Leshan–Liangshan–Zhaotong–Panzhihua–Chuxiong–Pu’er belt. (3) The alignment between tourism resources and rural tourism destinations is highest in Yunnan and Guizhou, while Chongqing exhibits the strongest match between destinations and tourism market potential and synergistic development conditions. Overall, 79.35% of rural tourism destinations in the region are situated within identified priority zones, with Chongqing, Guizhou, and Sichuan exhibiting the highest proportions. Based on the spatial mismatch between potential and existing destinations, the study delineates four development types—maintenance and enhancement, supplementation and upgrading, expansion, and reserve development—and offers regionally tailored planning recommendations. The proposed framework provides a replicable approach for spatial planning of rural tourism destinations in complex mountainous settings. Full article

As a pivotal node in urban spatial restructuring, the evolution of three-dimensional (3D) compactness in high-speed rail station areas is crucial for sustainable development. However, the existing research predominantly focuses on two-dimensional forms and lacks dynamic analysis and models that are adaptable to complex terrains. This study develops an enhanced 3D gravitational model that integrates satellite imagery and Gaode building data to quantify the spatiotemporal heterogeneity and carry out multidimensional classification of the compactness across 16 stations in the Chengdu-Chongqing urban agglomeration (2015–2025), with driving factors being identified through correlation and regression analyses. The key findings reveal the following: (1) The mean compactness increased by 22.41%, exhibiting nonlinear heterogeneity characterized by high initial values with low growth rates versus low initial values with high growth rates. Spatially, the southern line evolved from a dual-core pattern at the terminals to multigradient development, while the northern line maintained stable growth despite gradient discontinuities. These spatial differentiations resulted from synergistic effects of urban sizes (station hierarchy), terrain features, administrative divisions, and the line affiliation. (2) The built-up land area (under equal study conditions) and vertical development emerged as key drivers, with the building height diversity demonstrating dual spatial effects (enhancing both compactness and aesthetic richness). Complex terrain characteristics were found to promote clustered urban land use and compact efficiency during initial development phases. This study proposes a planning framework that integrates morphology-adaptive zoning control, ecology-responsive compactness principles, and urban–rural integrated settlement patterns, providing quantitative tools for mountainous station development. These findings offer theoretical and practical support for achieving urban sustainability goals and meeting the 3D compactness and transit-oriented development requirements in territorial spatial planning. Full article

Surface mining activities cause severe disruption to ecosystems, resulting in the substantial destruction of surface vegetation, the loss of soil organic carbon stocks, and a decrease in the ecosystem’s ability to sequester carbon. The ecological restoration of mining areas has been found to significantly enhance the carbon storage capacity of ecosystems. This study evaluated ecological restoration strategies in Chongqing’s Tongluo Mountain mining area by integrating GF-6 satellite multispectral data (2 m panchromatic/8 m multispectral resolution) with ground surveys across 45 quadrats to develop a quadratic regression model based on vegetation indices and the field-measured biomass. The methodology quantified carbon storage variations among engineered restoration (ER), natural recovery (NR), and unmanaged sites (CWR) while identifying optimal vegetation configurations for karst ecosystems. The methodology combined the high-spatial-resolution satellite imagery for large-scale vegetation mapping with field-measured biomass calibration to enhance the quantitative accuracy, enabling an efficient carbon storage assessment across heterogeneous landscapes. This hybrid approach overcame the limitations of traditional plot-based methods by providing spatially explicit, cost-effective monitoring solutions for mining ecosystems. The results demonstrate that engineered restoration significantly enhances carbon sequestration, with the aboveground vegetation biomass reaching 5.07 ± 1.05 tC/ha, a value 21% higher than in natural recovery areas (4.18 ± 0.23 tC/ha) and 189% greater than at unmanaged sites (1.75 ± 1.03 tC/ha). In areas subjected to engineered restoration, both the vegetation and soil carbon storage showed an upward trend, with soil carbon sequestration being the primary form, contributing to 81% of the total carbon storage, and with engineered restoration areas exceeding natural recovery and unmanaged zones by 17.6% and 106%, respectively, in terms of their soil carbon density (40.41 ± 9.99 tC/ha). Significant variations in the carbon sequestration capacity were observed across vegetation types. Bamboo forests exhibited the highest carbon density (25.8 tC/ha), followed by tree forests (2.54 ± 0.53 tC/ha), while grasslands showed the lowest values (0.88 ± 0.52 tC/ha). For future restoration initiatives, it is advisable to select suitable vegetation types based on the local dominant species for a comprehensive approach. Full article

Climate change has greatly affected the survival and distribution of various species. Understanding the distribution of species and their responses to climate change is helpful for species conservation and the utilization of germplasm resources. Carpinus fangiana is endemic to China, and it is used as an ornamental plant and in traditional Chinese medicine. However, its distribution remains unclear. In this study, we aimed to reconstruct the current and future ecological niches of C. fangiana. The prediction results indicated that annual precipitation and elevation are the key factors limiting its distribution. Our research found that it also exists in southern Chongqing and southwestern Hunan, and distinct suitable distribution areas and core suitable areas have been detected in these areas. Currently, the suitable distribution areas and core suitable areas of C. fangiana are mainly located in southwestern China around the Sichuan Basin. Although it is distributed in southeastern Yunnan, no distinct suitable distribution areas were detected there. In contrast, suitable distribution areas and core suitable areas were detected in the Qinling and Dabashan mountains, the mountainous areas in western Hubei, and southeastern Xizang, where C. fangiana is not currently distributed. Future climate change will likely have a considerable impact on its distribution, with a clear trend of suitable distribution areas migrating toward higher latitudes and elevations. The suitable distribution areas located in southeastern Xizang and northwestern Yunnan are expected to be lost in the future. In particular, under the high-concentration scenario, a substantial loss of suitable distribution areas is predicted. Full article

As a Chinese endemic species with dual medicinal–industrial importance, Eucommia ulmoides faces habitat challenges under climate change. Using 21 bioclimatic variables and 704 occurrence records, we modeled current and future (2021–2100) distributions via MaxEnt 3.4.4 and ArcGIS 10.8. The results indicate the following: (1) current optimal habitats cluster in the mid-elevation valleys of Daba–Wuling Mountains (Guizhou–Chongqing core); (2) SSP5-8.5 projections suggest a 19.2% reduction in high-suitability areas by 2081–2100 versus SSP1-2.6; and (3) distribution centroids migrate southward under both scenarios. Our multi-temporal analysis provides actionable intelligence for ex situ conservation and agroforestry planning. Full article

As China undergoes a rapid transition into an aging society, the mobility challenges faced by the older adults in high-density mountainous cities are exacerbated by complex topographical conditions. Existing studies often overlook the nonlinear relationships and the distinct planning requirements of mountainous versus flat urban areas when evaluating the age-friendliness of community parks. This study aims to identify the critical elements of age-friendly planning in mountainous community parks, validate the applicability of nonlinear models, and quantify the dynamic effects of various factors on older adults’ satisfaction, thereby establishing a foundation for targeted optimization strategies. Utilizing principal component analysis (PCA) on 358 valid questionnaires collected from three representative mountainous community parks in Chongqing, six key planning factors were extracted. An ordered logit model was employed for regression and marginal effect analyses. The findings reveal that (1) the ordered logit model outperforms alternative models in terms of goodness-of-fit and computational efficiency, making it particularly suitable for capturing the nonlinear characteristics of satisfaction; (2) accessibility facilities, spatial and social connectivity, and landscape environment emerge as the primary determinants of older adults’ satisfaction, with improvements in accessibility facilities exerting the most significant impact; and (3) the provision of multifunctional activity spaces and increased social opportunities effectively addresses the psychological and physiological needs of the older adults. This study contributes to the optimization of age-friendly design strategies for community parks in high-density mountainous cities, offering valuable insights for promoting healthy aging and fostering inclusive urban environments. Full article

Optimizing the habitat quality (HQ) assessment and revealing its nonlinear influence mechanisms, particularly by considering the mountain micro-topographic characteristics, are critically important for promoting sustainable development and safeguarding the ecological environment of mountain cities. Taking the Chongqing main city (CMC) as the study area, first, the Geomorphons algorithm was used to identify the mountain micro-topographic positions. On this basis, the HQ assessment of the InVEST model was optimized by collecting the multispectral data from UAV, and its spatiotemporal change trend was analyzed by the least-squares method. Secondly, hotspot analysis was used to explore the spatiotemporal differentiation of HQ on different land use and geomorphological types. Finally, based on the generalized additive model, the dominant influencing factors were determined, and their nonlinear effects were analyzed. The results showed the following: (1) The average HQ of the CMC showed an increasing trend from 2000 to 2020. The HQ of the four mountains and two rivers was higher, while it was lower in the central urban area. (2) The HQ hotspots were mainly distributed in parallel mountain areas and composed of forests, grasslands, and waters. The heterogeneity of HQ at the mountain micro-topographic scale was manifested in that the summits were always the hotspots of HQ. (3) HQ was influenced by a range of factors, including both natural environmental conditions and socio-economic drivers, among which the normalized difference vegetation index was the most important influencing factor. Full article

In recent years, there appears to be a notable transition towards preserving heritage on a regional scale, aiming to promote the authenticity and integrity of traditional settlements. The complex natural topography of these settlements, along with their spread-out arrangement, poses significant challenges to their protection and preservation. With the acceleration of urbanization and the implementation of the national strategy of building a twin-city economic circle in the Chengdu–Chongqing region, economic, cultural, and ecological exchanges between the twin cities have become the key dimensions of their construction. In this context, the concept of the BaShu Cultural Tourism Corridor has emerged, and the traditional settlement sites in the study area have become an important node of urban–rural integration and the BaShu Cultural Tourism Corridor. The primary objective of this study is to establish a heritage corridor protection network for traditional settlements along the Chengdu–Chongqing Ancient Post Road within the Sichuan Basin of China as an example, using the minimum cost resistance model. This approach comprises several key steps: selecting traditional settlements, analyzing their distribution traits, calculating the resistance value for the spread of traditional settlement culture, identifying potential cultural corridors, identifying cultural spaces, and, thus, constructing a protection network. The results show that the spatial distribution of traditional settlements in the study area shows obvious clustering characteristics, the core ecological space in this study is located in the mountains in the north and the southwest, and the cultural spaces are located along the central and southwestern sections, creating a linear distribution pattern. In the ecological culture corridor network, the Premier Corridor is the most extensive of the three categories, connects important cultural area, and serves as a vital conduit for developing heritage tourism strategies. This research aims to bolster the comprehensive protection and application of the region’s traditional cultural heritage, fostering the integration of urban and rural zones and enhancing regional cultural tourism. Future research directions are to integrate the conservation of traditional settlements and the surrounding environment at different planning scales with local policies and to expand the role of digital technology in the data management and visualization of ecocultural corridors. Full article

Landslide susceptibility evaluation is an indispensable part of disaster prevention and mitigation work. Selecting effective evaluation methods and models for landslide susceptibility assessment is of significant importance. This study focuses on selected areas in Yunyang County, Chongqing City. By interpreting high-resolution satellite remote sensing images from before and after heavy rainfall on 31 August 2014, the distribution of rainfall-induced accumulation landslides was obtained. To evaluate the susceptibility of accumulation landslides, we have equated evaluation factors to accumulation distribution prediction factors. Eight evaluation factors were extracted using multi-source data, including lithology, elevation, slope, remote sensing image texture features, and the normalized difference vegetation index (NDVI). Various machine learning models, such as Random Forest (RF), Support Vector Machine (SVM), and BP Neural Network models, were employed to assess the susceptibility of rainfall-induced accumulation landslides in the study area. Subsequently, the accuracy of the evaluation models was compared and verified using the Receiver Operating Characteristic (ROC) curve, and the evaluation results were analyzed. Finally, the developed Random Forest model was applied to Gongping Town in Fengjie County to verify its applicability in other regions. The findings indicate that the complex geological conditions and the unique tectonic erosion landform patterns in the northeastern region of Chongqing not only make this area a center of heavy rainfall but also lead to frequent and recurrent rainfall-induced landslides. The Random Forest model effectively reflects the development characteristics of accumulation landslides in the study area. High and very high susceptibility zones are concentrated in the northern and central regions of the study area, while low and moderate susceptibility zones predominantly occupy the mountainous and riverside areas. Landslide susceptibility mapping in the study area shows that the Random Forest model yields reasonably graded results. Elevation, remote sensing image texture features, and lithology are highly significant factors in the evaluation system, indicating that the development factors of slope geological disasters in the study area are mainly related to topography, geomorphology, and lithology. The landslide susceptibility evaluation results in Gongping Town, Fengjie County, validate the applicability of the Random Forest model developed in this study to other regions. Full article

Extreme rainfalls could greatly affect operations of urban rail transit systems of mountainous cities, which are prone to have landslides and floods under rainfalls. Therefore, it is essential to assess and enhance the resilience of mountainous urban rail transit networks under heavy rainfalls. Taking the metro network of Chongqing, the largest mountainous city in China, as an example, this study establishes a network topology model to identify the high-risk nodes under rainfalls and find the effective recovery strategies. By introducing the metro ridership and topological shortest distances, a network service efficiency function is developed, and the importance of nodes is quantified using service efficiency index and topological importance index. The resilience assessment model based on service efficiency is constructed using the resilience triangle theory. Additionally, risk levels for landslide and flood-prone areas are classified using the K-means algorithm, based on rainfall, elevation, and slope data, identifying high-risk stations. Finally, the node recovery sequence and strategies for high-risk nodes affected by landslides and floods are examined. The results indicate that in extreme rainfall scenarios, two transfer stations (Daping and Fuhua Road) are among the high-risk landslide stations, while most other nodes have a service efficiency index of less than 0.2. High-risk flood stations are located on non-transfer lines and mostly on metro lines with high traffic flow, with service efficiency index generally high, with some stations, like Bijin Station, exceeding 0.3. When all affected nodes fail, network service efficiency decreases by 84.0% and 75.2% under landslide and flood disasters, respectively. Compared with the random recovery strategy, recovery strategies based on topological importance and service efficiency index, the optimal recovery strategy based on genetic algorithm performs much better. Full article

Changes in species’ habitats provide important insights into the effects of climate change. Woonyoungia septentrionalis, a critically endangered species endemic to karst ecosystems, has a highly restricted distribution and is a key biological resource. Despite its ecological importance, the factors influencing its habitat suitability and distribution remain poorly understood. This study employed ecological niche modeling to predict the potential distribution of Woonyoungia septentrionalis across China and analyzed shifts in centroid location to explore migration pathways under current and future climate scenarios. The model exhibited high predictive accuracy (AUC = 0.988), indicating its robustness in assessing habitat suitability. Under current climatic conditions, Woonyoungia septentrionalis is predominantly found in the Guizhou–Guangxi border region, southeastern Yunnan, eastern Sichuan, southeastern Tibet, and parts of Chongqing, Hunan, and Hubei. Among these, the Guizhou-Guangxi border represents the primary suitable habitat. Temperature factors, particularly bio6 (minimum temperature of the coldest month) and bio7 (annual temperature range), were the most significant determinants of habitat suitability, contributing 43.29% and 12.65%, respectively. Soil cation exchange capacity (CEC) accounted for 15.82%, while precipitation had a relatively minor impact. Under future climate scenarios, suitable habitats for Woonyoungia septentrionalis are projected to shrink and shift toward higher altitudes and latitudes, increasing the risk of extinction due to the “mountain trap” effect, where migration is constrained by limited habitat at higher elevations. Stable habitats, particularly in Libo (Guizhou) and Huanjiang (Guangxi), are identified as critical refugia. We recommend prioritizing shrinking and stable habitats in Guizhou, Guangxi, and Yunnan for in situ conservation. Ex situ conservation efforts should focus on areas identified based on key environmental factors and predicted migration pathways to ensure the species’ long-term survival. This study provides both theoretical and practical guidance for the conservation of this species and its vulnerable habitat. Full article

Perilous rock mass disasters are typical forms of collapse disasters. Perilous rock masses are widely distributed in mountainous areas around the world and often pose a great threat to residents and line engineering. The correct evaluation of the stability and disaster-causing ability of perilous rock is important for the guarantee of sustainable development for human beings living in mountainous areas. The dynamic disaster effects of perilous rock collapse have always been a hot topic in the field of engineering geological disaster research. This study takes typical #WY8 and #WY47 perilous rock masses in a zone called the Jiaohua rock perilous rock zone in Chongqing, China, as a case study. The Jiaohua perilous rock mass is located in the Kaizhou District of the Three Gorges Reservoir area in China, which is mainly distributed in a ‘long strip’. The initial deformation and collapse of the perilous rock zone occurred in September 2004, and many local collapses have occurred since. In this study, the basic characteristics of the perilous rock belt of Jiaohua rock were first analyzed, and the failure mechanism of the perilous rock mass of Jiaohua rock was then summarized. Then, a numerical model of the perilous rock mass was established by DAN-W, and the disaster process of perilous rock collapse was analyzed. According to the characteristics of perilous rock and cliffs, considering the collapse partition, the collapse path of debris flow can be divided into three sections: the collapse section, slip section, and accumulation section. The calculation results show that the maximum velocity of the front edge of the #WY8 debris flow is 27.26 m/s, the maximum velocity of the trailing edge is 16.71 m/s, the maximum sliding distance is 437 m, and the impact force of the debris flow on the building is up to 52.29 kPa. The maximum velocity of the front edge of the #WY47 debris flow is 31.05 m/s, the maximum velocity of the trailing edge is 21.99 m/s, the maximum sliding distance is 194.31 m, and the impact force of the debris flow on the building is 241.15 kPa. Civil buildings within the scope of collapse are at risk of being completely destroyed. The research results of this study provide a certain theoretical basis for disaster prevention and mitigation work in the hidden danger area of rock avalanche disasters in the Three Gorges Reservoir area. Full article