Mountain City Research Articles

Assessment of Water Disaster Resilience in Mountainous Urban Metro Stations by Combination Weighting Method and Extension Cloud Model

Studying the resilience of metro stations in mountainous cities to heavy rain and flooding is of significant importance for enhancing the stability and safety of metro station operations. Considering the topographical and climatic characteristics of mountainous urban areas, this study analyzes the mechanisms through which heavy rain and flooding affect metro station resilience. Based on this analysis, 27 factors, influencing metro station resilience, are identified across 4 dimensions: absorptive capacity, resistance capacity, recovery capacity, and adaptive capacity. A water disaster resilience evaluation index system and corresponding rating standards are established for metro stations in mountainous cities. By combining the advantages of objective and subjective weighting, the combination weights of evaluation indicators are calculated using game theory. The extension theory is combined with the cloud model to establish a model for assessing the water disaster resilience of metro stations in mountainous urban areas. The applicability and feasibility of the model are validated through its implementation at Shapingba Station within Chongqing Rail Transit. The evaluation results obtained from the established model indicate a resilience level of IV for Shapingba metro station, reflecting a high level of resilience that aligns with real-world conditions. These findings further validate the proposed evaluation standards and the method for assessing the water disaster resilience of metro stations based on the combination weighting method and extension cloud model. This evaluation method considers the uncertainty in the evaluation process, demonstrating good feasibility and reliability. It offers a new perspective and methodology for assessing and analyzing the resilience of similar metro stations in mountainous cities.

Research on Landscape Design of Waterfront Public Space in Mountainous Cities Based on User Experience — Taking the Waterfront Landscape Design of Art Peninsula in Chongqing as an Example

Research on Landscape Design of Waterfront Public Space in Mountainous Cities Based on User Experience — Taking the Waterfront Landscape Design of Art Peninsula in Chongqing as an Example

Analysis and Validation of Sponge City Construction in Mountainous Cities based on SWMM - Taking Nanan District of Chongqing as an Example

Sponge city construction is one of the key topics in today’s research. China’s sponge city construction has gradually entered the stage of optimization and effect evaluation. However, there are still some gaps in issues such as the verification of the effect of sponge cities. Therefore, in this paper, Storm Water Management Model (SWMM) is carried out by collecting data on surface runoff, waterlogging, peak flow, control rate, etc. in Nanan District of Chongqing City. At the same time, reasonable Low Impact Developments (LID) facilities such as rain gardens, permeable paving, bioretention tanks, rain barrels, rooftop rainwater harvesting and rooftop gardens are incorporated into the sponge city design and verified by using a typical rainfall process with a return period of 5a and a duration of 3 hours. The results of the study showed that the surface runoff drainage time in one catchment was 11.1% faster before and after the LID facilities were installed in contrast, the peak flow reduction rate of the main pipe was 71.55%, and the average runoff control rate in each catchment was around 40.57%. In conclusion, the LID facilities are not effective enough to reduce the rainfall runoff above the medium rainfall, while they are more effective below the medium rainfall.

The spatial-temporal evolution patterns of landslide-oriented resilience in mountainous city: A case study of Chongqing, China

Cities, as complex systems with multi-interconnected subsystems, face significant challenges from both rapid urbanization and climate change. Ensuring high resilience in urban areas is essential for managing these dynamic risks effectively. This study introduces an innovative, data-driven approach to quantitatively analyze the spatial-temporal evolution patterns of urban resilience, validated through a case study of Chongqing, a representative mountainous city in China. Based on historical landslide data from Chongqing (2010–2020), which includes 4464 events, along with indicator data from the Chongqing Statistical Yearbook, we developed a comprehensive assessment framework. This framework incorporates 33 variables, covering indicators of physical-environmental resilience (PER) and socio-economic resilience (SER). The model integrates the Random Forest (RF) algorithm, Analytic Hierarchy Process (AHP), and Coupling Coordination Degree (CCD) model. Key findings include: (1) Social development in mountainous cities like Chongqing follows a point-to-area pattern. Although there is an overall increase in SER, the CCD in more developed areas (Chongqing urban circle) was generally higher than in less developed areas (northeastern and southeastern Chongqing) (2) The PER model demonstrated exceptional performance (AUC values consistently above 0.95). Spatiotemporal evolution models reveal that Chongqing maintains a high overall PER. Notably, from 2019 to 2020, the proportion of administrative units classified as highly resilient peaked at 24.5%, marking a historical high. (3) Multi-year average rainfall primarily impacts PER (ranked first), while Gross Domestic Product (GDP) significantly affect SER. The development of multi-dimensional recovery indicators provides a robust framework for assessing resilience against landslides in mountainous cities. The CCD model illustrates the importance of regional dynamic coordinated development in resilience trajectories. This study provides a detailed blueprint for the scientific development of resilient mountainous cities, emphasizing the need for a spatial-temporal perspective on resilience and the benefits of coordinated regional development.

WRF-HEATS coupling: Incorporating human behaviors and city topography into urban heat stress evaluation

Urban human thermal stress can be inaccurately estimated along with less-understood heat heterogeneity due to the absence of high-resolution meteorological information and realistic human behavior representation. To this end, we coupled a regional climate model (weather research and forecasting model, WRF) and a human energy balance model (human-environment adaptive thermal stress model, HEATS) to predict pedestrian's dynamic thermal stress at a neighborhood scale. The WRF-human coupling system resolves human-environment heat exchanges based on meteorological and topographical information with the consideration of dynamic human activities. The coupling system has been tested and utilized to study dynamic heat stress in a typical hot, humid, and mountainous city, Hong Kong. Our results revealed widespread heat heterogeneity with up to 7 °C difference in Physiological Subjective Temperature (PST) in the core urban area, and extreme heat exposure (up to 45 °C PST) in calm-wind zones at noon. Heat stress can be further aggregated considering realistic human behaviors such as extra clothing (e.g., protective facemask during pandemics) and physical exercise (e.g., walking along inclined terrain). Optimal-thermal-comfort routes have been designed and suggested based on the simulated neighborhood-scale heat stress map.

Progressive Collapse Performance of Prefabricated Step-Terrace Frame Structures in Mountain Cities

Progressive Collapse Performance of Prefabricated Step-Terrace Frame Structures in Mountain Cities

Motivations behind Active Sport Tourists Participating in Natural and Cultural Landscapes

Recreational running, both on roads and in mountains, is one of the most practiced physical activities worldwide, and so, the motivations behind participating have been quite extensively described in the literature. However, the cultural and environmental motivations behind these athletes traveling to other countries or destinations to compete have not been properly addressed yet. The aim of this research is to analyze the motivations of sport tourists and to compare the motivations that cause mountain runners and city runners to compete. A cross-sectional study with a total of 244 athletes, divided into a group of city marathon runners (N = 118) and a group of mountain ultra-marathon runners (N = 126), was conducted. Athletes completed the Sports Tourism Motivation Scale (STMS), composed of 37 items and nine dimensions, through an online survey. Participants were asked questions related to their age, running experience, distance to events, numbers of nights in hotels and volunteering. The results showed that there were statistically significant differences in four out of the nine dimensions of the STMS between city and mountain runners’ motivations and, likewise, statistical differences were found in some dimensions of the scale related to participants’ sex, age, running experience, numbers of nights in a hotel, travel distance and volunteering. In conclusion, the reasons why runners participate in mountain and city running events are different; likewise, some sociodemographic variables should be taken into account when organizing such sporting events in a sustainable way, in order to provide organizers with the most suitable information and attract the most participants.

Construction of Landscape Ecological Risk Collaborative Management Network in Mountainous Cities—A Case Study of Zhangjiakou

The prevention of ecological risks is a critical determinant influencing sustainable development. Driven by rapid socio-economic development, the ecosystems of mountainous cities within agro-pastoral transition zones are increasingly vulnerable to complex disturbances, constituting a significant threat to sustainable development and human well-being. To help achieve sustainable development, it is essential to conduct research on addressing and mitigating ecological risks from the perspective of collaborative management networks in mountainous cities. Taking Zhangjiakou as the study area, this paper employed the land use transfer matrix and standard deviation ellipse methods to analyze the dynamic land use changes. Additionally, using Fragstats 4,2 to calculate the landscape indices with land use data, this paper evaluated the landscape ecological risk (LER) from 2000 to 2020. Furthermore, the social network analysis (SNA) method was utilized to explore the spatial correlation characteristics of the LER. The findings indicate that: (1) Cultivated land and grassland were the predominant land use types in Zhangjiakou. During 2000–2020, Zhangjiakou experienced significant changes in land use, dominated by the transfer among cultivated land, forestland, and grassland. It indicated that the issue of unstable ecological land use continued to exist. Affected by human activities, construction land showed a consistent upward trend, primarily concentrated in the urban built-up areas and areas along the Jing-Zhang Railway. (2) The LER of Zhangjiakou was predominantly characterized by low risk, medium risk, and high risk levels. In the transitional areas and foothills, the LER was relatively higher. During 2000–2020, Zhangjiakou showed a declining trend of LER. This suggested that the ecological protection policies in Zhangjiakou were effective, leading to an improvement in the local ecological environment. (3) The LER in Zhangjiakou demonstrated a spatial clustering pattern that exhibited an upward trend, which was supported by both spatial autocorrelation and the SNA analysis. In the LER collaborative management network, Xuanhua, Qiaodong, Qiaoxi, Wanquan and Zhangbei consistently upheld pivotal roles. Based on the number of inward and outward connections, 16 counties in Zhangjiakou were classified into four categories and three zones accompanied by corresponding recommendations. The findings of this study can serve as a valuable reference for subsequent landscape pattern optimization and ecological restoration in Zhangjiakou.

Assessing spatio-temporal heterogeneity and drivers of ecosystem services to support zonal management in mountainous cities

With complex topography and geomorphology, mountainous cities possess abundant natural resources. They are constrained by ecological environment and topographic conditions, leading to a prominent contradiction between urbanization development and ecological protection. As a result, ecosystem services (ESs) are under greater regulatory pressure. The identification of ecosystem services bundles (ESBs) can be the foundation for developing zonal ecological protection planning policies. We took Chongqing as a case study, investigated the impact mechanisms of socio-ecological factors on the level of ES supply in each ESB. The findings reveal that: (1) The quantitative assessment of ESs for 2000, 2010, and 2020 showed that ESs were temporally stable and spatially heterogeneous. Areas with high supplies of food production (FP) and water yield (WY) were predominantly found in the northwestern cropland and urban built-up regions, whereas high supply areas for the other four ESs were primarily located in the northeastern Dabashan Mountains and the southern Wuling Mountains. (2) The quantification of trade-offs and synergies between ESs showed that FP had a trade-off effect with all five other ESs, while most other ES pairs exhibited synergistic effects. It was found that the interrelationships produced changes over time. (3) Then, three types of ESBs were identified. After examining the influence mechanisms of socio-ecological factors across the three ESBs, individual ESs were found to have essentially the same types of main impact factors in three ESBs, but varies in impact. (4) Finally, with reference to changes in ES levels and interrelationships and the driving mechanisms of socio-ecological factors in each zone, this study proposed zonal strategies for managing ecosystem services and optimizing territorial space based on the geographic characteristics and socio-economic development in different ESBs, with the goal of attaining sustainable urban development and improving human welfare.

Population Distribution in Guizhou’s Mountainous Cities: Evolution of Spatial Pattern and Driving Factors

Guizhou is a typical mountainous province and is also one of the lowland regions in China that has attracted a population influx. Here, using population density data from 2000 to 2020 as the basic dataset and the coefficient of variation method and standard deviation ellipse analysis, we investigated the spatial characteristics across different years. The results show: Firstly, Guizhou’s population has a distinct spatial distribution, characterized by a lower population density in the southeast and a higher density in the northwest as well as an increasing polarization of population concentration toward the centers of prefecture-level cities and provincial capitals. Fluctuations in population density resemble a central siphon effect, which is particularly pronounced in the provincial capital and show a significant gravitational pull. Secondly, the coefficient of variation in population density across Guizhou’s counties is spatially divided by Guiyang, showing higher values in the east and lower values in the west. Furthermore, the ellipse of the standard deviation of population density is gradually shrinking, indicating an increasingly concentrated population distribution. Thirdly, the explanatory power of the population and socio-economic systems on the population distribution in Guizhou is significantly greater than that of the natural systems. Population distribution and migration patterns have shifted from purely “economic driven” to coexisting with “economic and comfort-oriented” trends, and there is an urgent need to improve the comfort level of public services as a typical supply, in order to boost Guizhou’s population attraction.

Identification of influencing factors and risk assessment of underground space flooding in the mountain city

As a consequence of the process of urbanization, there is an increasing reliance on and exploitation of underground spaces. Moreover, these areas are susceptible to urban waterlogging, which can be difficult to drain, potentially leading to significant risks. At present, there are few simulations in hydrodynamic models that consider underground spaces. The risk of inundation of underground spaces remains an uncertain phenomenon. This study conceptualized underground spaces as storage areas, with the aim of simulating the spatial distribution of flood risk for different return periods. We studied the flooding processes and characteristics of three underground space types. The results indicate that the flood evolution simulated by the simplified modeling method that incorporates underground space is more aligned with the actual situation. To further analyze the risk distribution of urban waterlogging, we choose the XGBoost model and SHapley Additive exPlanations (SHAP) method to assess the influence of specific indicators on the occurrence of urban waterlogging in mountainous regions. Our analysis revealed that key factors include density of road (DR), flow velocity (V), density of pipes (DP), elevation (DEM), and inundation height (H), with contribution rates of 23.13 %, 17.06 %, 14.67 %, 10.12 %, and 9.04 %, respectively. This analysis clarified the risk of underground inundation within the study area, which can serve as a reference point for the formulation of flood control and drainage strategies.

The Impact of Population Shrinkage on Economic Resilience in Mountain Cities: A Case Study of Guizhou Province, China

With the recent changes in population structure and continuous urbanization, the degree of population shrinkage in mountain cities has increased, especially under the impact of the COVID-19 epidemic, and the economic development of such mountain cities has become a prominent issue. The epidemic has not only exposed the vulnerability of these cities to economic development but also aggravated the negative impact of population contraction, bringing about new challenges and pressures related to regional population development and economic resilience. This change has become an important topic in the study of mountain cities. Therefore, taking Guizhou Province as a case study, this work applies the population change rate, the entropy method, and a mediation effect model to study the spatiotemporal evolution of population shrinkage and economic resilience, and it explores how population shrinkage influences economic resilience. The results reveal the following: (1) Few counties experienced population shrinkage in Guizhou Province from 2013 to 2017, indicating a sporadic distribution pattern, whereas the degree of population shrinkage increased rapidly from 2018 to 2022, revealing an east–west symmetrical distribution pattern, with Guiyang city located on the central axis. (2) There are significant regional differences in the spatial distribution of the level of economic resilience between the two periods. Under the impact of COVID-19, from 2019 to 2022, although the overall level of economic resilience increased, the level of resilience in most counties tended to decrease. (3) Regarding the mediating effect, population shrinkage affected the level of economic resilience through general public budget expenditure, foreign trade investment, new urban employment, and GDP. The abovementioned findings are helpful for providing theoretical support and empirical guidance for the sustainable development of mountain cities in the face of population contraction, economic challenges, and promoting regional coordination.

Spatial-temporal pattern of ecosystem services and sustainable development in representative mountainous cities: A case study of Chengdu-Chongqing Urban Agglomeration

The Sustainable Development Goals (SDGs) are essential measure for preserving the balance between human well-being and natural ecosystems. The benefit of preserving ecosystems health play a crucial role in promoting the SDGs by providing stable ecosystem services (ESs). However, the ecological health of mountainous cities is vulnerable, with relative low ecological resilience. To investigate the conflict between ecosystems and sustainable development, this study takes the Chengdu-Chongqing Urban Agglomeration as the study area. The major tasks and results in this study include: (1) using the entropy weighting method and the InVEST model, we combined remote sensing, geographic, and statistical data to quantify three types of SDGs (economic, social, environmental) and four ESs (water yield, soil conservation, habitat quality, carbon storage), and establish a localized sustainable development assessment framework that is applicable to the Chengdu-Chongqing Urban Agglomeration. The results show that from 2014 to 2020, the three types of SDGs exhibited an overall upward trend, with the lowest values occurring in 2016. The gap between different counties has narrowed, but significant regional differences still remain, indicating an unbalanced development status quo. Among the 142 counties, water yield and soil conservation values show a consistent downward trend but occupies significant interannual variations, while habitat quality and carbon storage values increases consistently each year. (2) using Spearman's nonparametric correlation analysis and multiscale geographically weighted regression model to explore the temporal variation and spatial heterogeneity of correlations between county ESs and SDGs. The results showed significant heterogeneity in the spatial trade-offs and synergies between ESs and SDGs, with two pairs of synergies weakening, seven pairs of trade-offs increasing, and the strongest negative correlation between Economic Sustainable Development Goals and habitat quality. (3) we applied the self-organizing mapping neural networks to analyze the spatial clustering characteristics of ESs-SDGs. Based on the spatial clustering effects, we divides the Chengdu-Chongqing Urban Agglomeration into four zones, and different zones have different levels of ESs and SDGs. The targeted strategies should be adopted according to local conditions. This work is of great practical importance in maintaining the stability and sustainable development of the Chengdu-Chongqing Urban Agglomeration ecosystem and provides a scientific reference for the optimal regulation of mountainous cities.

Insight into the Probiogenomic Potential of Enterococcus faecium BGPAS1-3 and Application of a Potent Thermostable Bacteriocin.

This study aimed to investigate the probiogenomic features of artisanal bacteriocin-producing Enterococcus faecium BGPAS1-3 and the use of the improved pMALc5HisEk expression vector for overexpressing class II bacteriocins and the application of purified bacteriocin 31 in a milk model as a preservative against L. monocytogenes. The BGPAS1-3 strain was isolated from traditional fresh soft cheese manufactured in households on a small scale in rural locations surrounding Pale Mountain City in Bosnia and Herzegovina. The whole-genome sequencing approach and bioinformatics analyses revealed that the strain BGPAS1-3 was non-pathogenic to humans. The presence of bacteriocin operons suggested the ability of the isolate to suppress the growth of pathogens. Coding regions for three maturated bacteriocins (bacteriocin 31, bacteriocin 32, and enterocin P) produced by BGPAS1-3 were amplified and expressed in Escherichia coli ER2523 using the pMALc5HisEk system. All three bacteriocins were successfully overexpressed and purified after enterokinase cleavage but showed different antimicrobial activity. Bacteriocin 31 showed significantly stronger antimicrobial activity compared with bacteriocin 32. It was the only one that proved to be suitable for use as a food preservative against L. monocytogenes in a milk model.

Quantifying the influences of landscape gradient on urban spatial efficiency by using surface metrics in the central area of a mountainous city

Rapid urbanization in mountainous areas has caused unbalanced development, land use conflicts, and decreased urban spatial efficiency (USE) due to terrain constraints and disorderly land expansion, and this issue has not been fully explored. To address this gap, this study constructs a framework to quantify the impacts of landscape gradients on urban spatial efficiency. By developing indicator systems to characterize both landscape heterogeneity and urban spatial efficiency, the relationships between these factors are analyzed using the Boosting Regression Trees model, and clusters are identified to reveal spatial differentiation through key landscape gradient indicators. The results indicate that (1) the Summit Density (Sds) of Normalized Difference Vegetation Index (NDVI) exhibits the most significant negative impact on urban spatial efficiency, especially on spatial utilization efficiency; (2) the Root Mean Square Slope (Sdq) of Digital Elevation negatively affects traffic and public services efficiency; (3) the Texture Direction Index (Stdi) of building distribution has the most significant positive impact on public service efficiency. In mountainous environments, different landscape gradient types exhibit clear contrasts in urban spatial efficiency. Varied elevations lead to diverse construction sites and building layouts within urban blocks, resulting in spatial differentiation of urban spatial efficiency. This study enhances the use of gradient surface metrics in urban spatial research by describing landscape patterns and heterogeneity at the block scale. It offers valuable insights for urban planning and design with a focus on equity and sustainability.

Assessing Eco-Environmental Effects and Its Impacts Mechanisms in the Mountainous City: Insights from Ecological–Production–Living Spaces Using Machine Learning Models in Chongqing

In the face of accelerating land use changes, conflicts between land use patterns and the eco-environment are increasingly pronounced. By calculating the eco-environment quality index (EQI) adopting the ecological–production–living spaces (EPLS) framework, we evaluate the eco-environment quality of land use changes within Chongqing’s central urban area from 2000 to 2020. The study employs a random forest model to elucidate the mechanisms influencing the eco-environment quality. The findings reveal the following: (1) Living spaces have expanded by 361.53 km2, while production and the ecological spaces have been experiencing a significant reduction of 331.42 km2 and 30.11 km2 over two decades. (2) The eco-environment quality has steadily declined from 0.3665 in 2000 to 0.3501 in 2020, indicating a degradation in overall quality. There is notable spatial variation in eco-environment quality, typically displaying a “low center–high periphery” pattern. (3) Pesticide usage, grain production, and the added value of the primary industry are the primary factors affecting ecological quality. The findings of this study provide valuable insights for global urban planning and environmental management. Rapidly, land use change regions worldwide face similar conflicts between economic growth and ecological sustainability. This research underscores the need for integrated land use policies that balance development with environmental preservation. The methodologies and findings can inform international efforts to optimize land use patterns, improve ecological quality, and achieving sustainable development goals, offering adaptable strategies for policymakers and urban planners globally.

Characteristics of and Protection and Utilization Strategies for Cliff Landscapes in Mountain Cities: A Case Study of the Two Rivers and Four Banks Area in Chongqing

Characteristics of and Protection and Utilization Strategies for Cliff Landscapes in Mountain Cities: A Case Study of the Two Rivers and Four Banks Area in Chongqing

Spatial Identification and Risk Assessment of High-Temperature Heat Wave Disasters in Mountain Cities: A Case Study of Chongqing

Spatial Identification and Risk Assessment of High-Temperature Heat Wave Disasters in Mountain Cities: A Case Study of Chongqing

Planning nodes, places, and pedestrian experiences in mountainous cities: an empirical transit station assessment tool

IntroductionIn the context of ongoing discussions in Chongqing (China) about urban development strategies for the city’s transit system, this paper introduces an empirical framework for assessing the development of urban transit stations in mountainous cities. Cities in mountainous areas possess unique natural topography, development patterns, cultures, and natural resources, leading to distinct urban development characteristics compared to cities built on plains.MethodsDrawing on the node-place modelling literature, we develop a multidimensional station assessment methodology adapted for mountainous cities. By adding the dimension of pedestrian experience, we propose indicators that represent the unique challenges of accessing stations in such terrains that are not typically reflected in conventional node-place analysis.ResultsOur findings reveal station-specific development opportunities in greater detail and can guide more targeted planning for land use around stations.DiscussionOur assessment method is particularly useful for cities facing terrain challenges that impact pedestrian experience.

Characteristics and Influencing Factors of Landscape Pattern Gradient Transformation of Small-Scale Agroforestry Patches in Mountain Cities

Small-scale agroforestry patches possess irreplaceable value compared to large-scale patches. In southwestern mountainous cities of China, the complex terrain and urbanization have led to the presence of numerous small, fragmented agroforestry patches around urban areas. These patches serve as crucial habitats for endemic species and provide essential space for wild food sources, thereby contributing to a range of ecosystem services. Consequently, their proper conservation and utilization planning are of paramount importance. This study investigates the transformation characteristics of landscape patterns of mountainous small-scale agroforestry patches and their constituent elements across urban–rural gradients, identifying the driving factors behind these transformations to support conservation and utilization planning. From an urban–rural gradient perspective, four directional transects were selected and divided into uniform sample grids. Using Fragstats 4.3, landscape indices of small-scale agroforestry patches were calculated, analyzing the transformation characteristics of these patches and their elements across different gradients. Spearman correlation coefficients in SPSS were employed to assess the influence of terrain and relevant anthropogenic factors on the transformation of agroforestry patches. The findings reveal the following: (1) Small-scale agroforestry patches and their elements exhibit similar patterns in terms of size, fragmentation, dispersion, and connectivity, showing an “increasing trend in size and connectivity, decreasing fragmentation, and fluctuating dispersion” from urban centers to natural areas, with slight variations in orchard patches. However, patch cohesion and shape complexity display nonlinear differentiated transformation characteristics. (2) Overall, small-scale agroforestry patches are significantly influenced by anthropogenic construction factors, with the landscape pattern of forest patches notably affected by terrain factors. (3) Across urban–rural gradient zones, the landscape patterns of small-scale agroforestry patches in urban centers, suburbs, and rural natural areas are more affected by terrain factors, whereas those in urban construction zones are significantly influenced by anthropogenic construction factors. The findings of this study provide a scientific basis for the conservation and planning of mountainous small-scale agroforestry patches.