Degree Of Coordination Research Articles

Multi-Scale Supply and Demand Relationships of Ecosystem Services Under Multiple Scenarios and Ecological Zoning to Promote Sustainable Urban Ecological Development in Arid Regions of China

Predicting and analyzing the supply and demand relationship of ecosystem services provides theoretical support for the improvement of the ecological environment. This paper takes Bortala, a typical oasis city with a fragile ecological environment in the arid northwest region, as a case study. Based on the GMOP-PLUS-InVEST coupled model, it predicts the coupling coordination and matching degree of the supply and demand connection of ecosystem services such as habitat quality (HQ), carbon storage (CS), water yield (WY), and soil erosion (SD) under four scenarios. The findings indicate that from 2020 to 2035, HQ, CS, and WY have basically achieved coupling coordination at both scales. However, there is a notable disparity in the supply and demand of water resource production and carbon emission production. To ensure the long-term balance of ecosystem service supply and demand (ESSD), the research area was ultimately divided into five ecological zones: ecological conservation zone, ecological agriculture zone, ecological moderate development zone, ecological improvement zone, and ecological protection zone. It could offer insights for guiding the sustainable growth of ecologically vulnerable zones in the future.

Long-term alfalfa planting mediates the coupling of soil water and organic carbon storage in a semi-arid area of the Loess Plateau, China

The key to restoring arid and semi-arid ecosystems is maintaining soil water and organic carbon contents. Alfalfa (Medicago sativa L.) is a high-yield perennial forage crop and performs ecological functions as a drought-resistance leguminous herb. It has been widely planted for reconstruction of degraded soils in the Loess Plateau in northwestern China, but long-term planting may affect soil carbon–water coupling and lead to crop yield reduction. To maximize the benefits of reconstructed grassland, this study explored the couplings of soil water, organic carbon, and alfalfa productivity along a reconstruction chronosequence in a semi-arid area of the Loess Plateau. Space-for-time substitution approach was used to select different-aged stands of reconstructed grassland (1, 5, 7, 10, 15, 20, 30 years old). Alfalfa above-ground biomass (AGB), soil water storage (SWS), organic carbon storage (SOCS), and carbon–water coupling coordination degree (D) were measured in the 0–100 cm soil profile. Alfalfa AGB reached a peak in the 7th year, and the degradation began in the 10th year. Both SWS and SOCS varied nonlinearly with stand age. The greatest loss of SWS occurred in the 15th year (80–100 cm depth), whereas the largest increase of SOCS occurred in the 30th year (0–20 cm depth). There was a negative feedback relationship between AGB and SWS over the 30-year study period (Pearson r = −0.835, P = 0.098). AGB and SOCS initially showed a trade-off within the first 10 years (Pearson r = −0.7431, P = 0.2569), in contrast to their positive feedback in the 20–30th years (Pearson r = 0.9978, P = 0.0421). A decoupling between SWS and SOCS (D < 0.6) was observed after 12 years of alfalfa planting. For agricultural production, a greater supply of water and organic fertilizer is required from the 7th year of alfalfa planting, and reseeding may be needed around the 10th year to prolong the life of alfalfa community. Alfalfa should be planted for no more than 12 consecutive years in the study area for ecological protection.

Spatial Coordination Analysis and Development Methods of the Catering Sector in Yongkang City

The catering sector is recognized as a crucial driver for stimulating domestic consumption and fostering sustained economic growth. A scientifically informed spatial planning of the catering sector in county-level cities can help mitigate the overconcentration or excessive dispersal of resources, thereby enhancing the efficiency of land and commercial resource utilization, reducing waste, and promoting sustainable development within a county’s economy. This study focuses on Yongkang City, located in central Zhejiang Province, as a case study. Using Python 3.1 software to extract point-of-interest (POI) data, spatial analysis techniques such as standard deviation ellipses and kernel density estimation are employed to elucidate the spatial distribution characteristics of the catering sector, comprehensive transportation, and public services in Yongkang City. Furthermore, a coupling coordination degree model is utilized to quantify the coupling coordination degrees between the catering sector and comprehensive transportation (D1), as well as between the catering sector and public services (D2), ultimately assessing the overall coupling coordination degree among the three sectors (D3). Based on the analysis results, the coupling coordination degrees are categorized into five levels, followed by a detailed evaluation of the catering sector’s development across different subdistricts. The findings indicate a certain degree of spatial imbalance in the distribution of the catering sector in Yongkang City, with the western region exhibiting a more favorable development trajectory. Notably, Dongcheng Subdistrict achieved the highest coupling coordination degree (0.993), while the northern region, hindered by underdeveloped economic conditions and limited transportation infrastructure, exhibited the lowest coordination degree (0.098). Considering the unique developmental characteristics and current conditions of each subdistrict, this study advocates for the formulation of a long-term sustainable development plan for the catering sector in Yongkang City. The findings of this research may offer valuable insights for other regions and countries, thereby promoting the sustainable advancement of the catering sector.

Spatiotemporal differentiation and influencing factors of the degree of resilience coupling coordination in the Beijing–Tianjin–Hebei region, China

Urban agglomeration system resilience involves multiple subsystems that are interconnected and interactive, and exploring the relationships among subsystems can elucidate and increase urban agglomeration resilience. This study constructed a social-economic-built environment resilience model and proposed a social-economic-built environment resilience index system. Using the entropy weight method, the coupling coordination degree (CCD) model, GeoDetector, spatial autocorrelation analysis and the autoregressive integrated moving average model (ARIMA) model, the resilience development level of the Beijing‒Tianjin‒Hebei (BTH) region from 2000 to 2020 was evaluated, the main influencing factors for the spatiotemporal differentiation pattern were identified, and the development levels in 2030 and 2050 were predicted. The results show that (1) high-resilience and high-CCD regions are concentrated in the region of Beijing and Tianjin in the centre, and low-value regions are concentrated in the districts and counties in the west and south; (2) economic elements, especially the economic aggregate status of a region as a whole, are the main factors contributing to the differences in resilience levels between regions, but their influence gradually decreases; and (3) the gap between the CCDs of Beijing, Tianjin and cities in Hebei increased from 2000 to 2020, but this gap is expected to narrow by 2030 and 2050. On this basis, five categories of future development guidelines for cities in the BTH region are proposed.

Role of inclusion clusters on fatigue crack initiation in powder metallurgy nickel-based FGH96 superalloy

Inclusion clusters with a size of several tens of micrometers were found to be inclined to early crack initiation, resulting in an abnormally reduced fatigue life. Fatigue tests were conducted to elucidate crack initiation behaviors of inclusion clusters in nickel-based powder metallurgy (P/M) FGH96 superalloy. The inclusion clusters with varying sizes and shapes located at grain boundaries are composed of Al2O3, MgO and ZrO2 particles. The inclusion cluster with large size within 25-35 μm, small average particle distance within 0-4 μm and large orientation relative to loading direction within 35-66° will be more likely to cause crack initiation. In particular, the inclusion clusters with large size and high aggregation degree experience extruding during processing and subsequent heat-treatments due to the difference in thermal expansion coefficient with the matrix behave multiple cracking before fatigue loading, thereby facilitating crack initiation in the surrounding matrix grains. Moreover, as the main cracking part of inclusion clusters, the Al2O3 particles exhibit self-cracking and interface debonding, owing to higher hardness and poorer deformation coordination degree with matrix compared to other component inclusion particles.

Coupling and coordination of food security and agricultural carbon emission efficiency: Changing trends, influencing factors, and different government priority scenarios

Seeking a balance between food security and carbon mitigation is key to achieving sustainable agricultural development. This study evaluates the coupling coordination degree (CCD) between the food security index (FSI) and agricultural carbon emission efficiency (ACEE) in China from 2010 to 2021 using the coupled coordination model. By adjusting the model coefficients, different government priority scenarios are simulated to explore their impact on CCD. The Geodetector method is employed to identify the influencing factors of CCD, investigate their interactions, and assess the differences in these factors across various government priority settings. The average CCD between FSI and ACEE exhibits a notable upward trend, rising from 0.4583 in 2010 to 0.6595 in 2021. Furthermore, regional disparities are widening, particularly in the major production areas. Catch-up effects exist within regions. Policy simulations showed staged interactions between food security and agricultural carbon efficiency, shifting from food security to balanced production and ecology, then to prioritizing low-carbon production for food security. Adjusting policy priorities can effectively improve coupling coordination in the short term, with increasing impact as priority shifts. CCD is influenced by policy, technology, economy, and society, varying with policy priorities. In the baseline scenario, key factors for CCD include the urban-rural income gap, technological advancement, urbanization, and farmers' education level. When the government prioritizes food security, the impact of narrowing income gaps and agricultural industry agglomeration becomes more pronounced. Conversely, emphasizing carbon emission efficiency enhances the influence of technological advancements and urbanization on CCD. Tailoring agricultural production strategies to local conditions and emphasizing interactive effects among factors is crucial for achieving environmentally friendly and high-quality agricultural development goals.

Influence of Digital Economy on Ecological Carbon Environment in North China Under Spatiotemporal Synergistic Evolution

North China is one of the significant geographic subregions in China, and it is quite important to analyze its digital economy and ecological carbon environment. Firstly, the digital economy level and ecological carbon environment in North China between 2010 and 2019 were measured. Then, the coupling coordination degree model (CCDM) was utilized to examine the impact of the digital economy on the ecological carbon environment. The digital economy level in North China consistently increased between 2010 and 2019. The average value rose from 0.163 in 2010 to 0.645 in 2019. Moreover, carbon emission intensity showed a year-on-year decrease, with an average reduction of 23.47% during the same period. The degree of coupling coordination displayed an upward trend, and Beijing showed the highest coordination among all provinces and cities. These results highlight the impact of the digital economy level on the ecological carbon environment. Some suggestions were proposed for the future progress of the digital economy and carbon emission in North China.

Construction of a Competency Evaluation Indicator System for Specialist Nurses in Liver Transplantation: A Delphi Study.

Liver transplantation specialist nurses provide comprehensive and safe care for liver transplant patients, which requires them to have a wide range of competencies. However, at present, there is no comprehensive understanding of the competency of liver transplantation specialist nurses in China, and there is a lack of comprehensive evaluation indicators. The purpose of this study was to construct a competency evaluation indicator system for specialist nurses in liver transplantation. Utilizing the "Iceberg model" of competency, the indicator system for evaluating the competency of liver transplant specialist nurses was developed through literature review, semi-structured interviews, and two rounds of Delphi expert consultation. Twenty nursing and medical experts in liver transplantation were consulted over two rounds. The effective response rates for the expert consultation questionnaires were 90.91% and 100.00% for the first and second rounds, respectively. The coefficient of expert judgment was 0.920, the coefficient of familiarity was 0.880, and the authority coefficient was 0.900. The value range of the coefficient of variation in the second round was 0.00-0.16, both <0.25, indicating that the degree of coordination of expert opinions was high. The final competency evaluation index system for liver transplant specialist nurses encompassed 6 primary indicators, 17 secondary indicators, and 59 tertiary indicators, including professional knowledge, professional skills, social role, self-concept, personality quality, and motivation. The developed competency evaluation indicator system for liver transplant specialist nurses possesses scientific validity and reliability, offering a reference for the training and assessment of liver transplant specialist nurses.

Mutual Causality Between Urban Transport Superiority Degree and Urban Land Use Efficiency: Insights from County Cities in Gansu Province Under the Belt and Road Initiative

Exploring the coupled coordination and interaction between urban transport superiority degree (UTSD) and urban land use efficiency (ULUE) is the key to promoting efficient land use in cities and coordinated development. This paper adopts the improved UTSD model, super-efficiency slack-based measure–undesirable output model, coupling coordination degree model (CCDM), panel Granger causality test, random forest model, and the mixed geographically and temporally weighted regression model to reveal the spatial and temporal evolution and coupling characteristics of UTSD and ULUE in Gansu from 2005 to 2020 and to validate and explore the interaction mechanism between UTSD and ULUE. The results show that (1), from 2005 to 2020, the average UTSD in Gansu increased from 0.56 to 1.01 and the Belt and Road Initiative accelerated the construction of the transportation network in Gansu. The average ULUE increased from 0.52 to 0.62; the spatial distribution of ULUE was high in the west and north and low in the east and south. (2) From 2005 to 2020, the average CCDM of UTSD and ULUE in Gansu increased from slightly unbalanced (0.37) to slightly balanced (0.52). A spatially high UTSD and high ULUE agglomeration area can be found along the transportation arteries. (3) The UTSD and ULUE were mutually causal, with the degree of transportation arterial influence degree being the strongest driver of ULUE among the components of UTSD (30.41% contribution) and tax revenue being the strongest driver of UTSD among the components of ULUE (15.10% contribution). Overall, the connotation of ULUE puts forward the demand for improving the transportation infrastructure and, at the same time, provides the guarantee for UTSD upgrading, which in turn affects the ULUE. In the future, the Xinan region of Gansu should prioritize planning and construction of a transportation network. The results of this study can provide a scientific basis for the construction of transportation networks and the efficient use of urban land in Gansu and other regions.

Coupling Coordination Relationships Between Ecosystems and Economic Development in Qinghai and Tibet

The coordinated development of ecological protection and socioeconomics in the Tibetan Plateau is of great significance. This study examines the coupling coordination of urban ecosystems and economic development across 15 municipal administrative units in Qinghai Province and the Tibet Autonomous Region, the core areas of the Tibetan Plateau. The findings reveal that a larger proportion of the Qinghai and Tibet ecosystems are classified above the medium vulnerability level, primarily due to inherent natural geographic conditions. Additionally, the area of the two provinces and regions below the medium development level is larger, which is mainly influenced by indicators of economic strength and industrial structure. The degree of coupling coordination between the ecosystem and economic system in Qinghai and Tibet is predominantly driven by economic factors. Given the existing natural environmental conditions, the eastern regions of Qinghai and Tibet still possess certain development potential, while the economic development in the western areas is somewhat constrained by the natural environment. Based on this, further policy recommendations have been proposed to adjust and upgrade the industrial structure, aligning ecological protection with economic development in the Qinghai–Tibet Plateau. These recommendations aim to facilitate the formulation of strategies and policies for sustainable urban construction and social development in such high-ecological-value regions as the Tibetan Plateau.

Impact of land-use change on coupling coordination degree of regional water–food–carbon system

IntroductionThe objective of this study is to investigate the impact of land use changes on the coupling coordination of the regional water-food-carbon system in Hebei Province. Moreover, the findings aim to offer insights for achieving comprehensive and coordinated development of regional resources.MethodsBy constructing an evaluation index system of the coupled coordinated development of the water-food-carbon system, using the coupled coordination model to study the coupled coordination of the water-food-carbon (WFC) system in Hebei Province from 2010 to 2020, and applying the Pearson correlation coefficient and ArcGIS to analyze the impacts of land-use changes on the degree of coupled coordination.ResultsThe results show that: (1) The most notable characteristics of land type changes include a decrease in cropland and an increase in construction land, primarily driven by the conversion of cropland to construction sites. The total area converted amounts to 8207.20 km2. (2) The degree of coupled coordination of the water-food-carbon system in the study area as a whole shows an upward and then downward trend, and shows a spatial distribution pattern of “high in the north-east and low in the south-west”; (3) In Hebei Province, the degree of coupling coordination within the water-food-carbon system exhibits a stable positive correlation with forest land, grassland, and water area. Additionally, the transfer of forest land and grassland are significant factors influencing the delineation of cold and hot spots within the region.DiscussionTherefore, in addressing the coordinated development of the water-food-carbon system, it is essential to consider the influence of land. Resources should be allocated judiciously based on regional advantages to promote sustainable development effectively.

Coupling Coordination and Influencing Factors Between Digital Village Development and Agricultural and Rural Modernization: Evidence from China

With the increasing application of new digital technologies in rural areas, digital village development has become a crucial pathway for achieving agricultural and rural modernization. This study develops a comprehensive measurement index system to assess the levels of digital village development and agricultural modernization. Then, the coupling coordination model is adopted to measure the coupling coordination development levels of digital villages and agricultural modernization across 266 prefecture-level cities in China from 2014 to 2020. Additionally, the driving mechanisms of the coupling coordination degree are also explored based on the geographic detector model. The results show that the overall levels of digital village development and agricultural and rural modernization in China are on an upward trend. The coupling coordination degree of the two systems has shifted from being on the verge of imbalance to primary coordination. Additionally, absolute regional differences have widened, while relative differences have narrowed. Ecological livability, management systems, living standards, informatization, and mechanization levels are identified as the key factors driving the coupling coordination between digital village development and agricultural modernization. These results offer valuable insights for both theoretical research and practical applications in advancing digital villages and agricultural modernization efforts.

Green Technology Innovation and Carbon Emission Performance of the Middle Reaches of the Yangtze River Urban Agglomeration: Mechanism and Spatio-Temporal Evolution

Amid the increasingly severe global climate change situation, green technology innovation has become an important means to promote carbon reduction and achieve the transition to a low-carbon economy. This study aims to systematically analyze the relationship between green technology innovation and carbon emission performance in the urban agglomeration of the middle reaches of the Yangtze River, exploring the degree of coupling and coordination between different cities. Utilizing data from 2011 to 2021, we employ methods such as the Coupling Coordination Degree Model and fixed effects model to achieve our objectives. Our findings reveal that both green technology innovation and carbon emission performance in this region are on an upward trend; however, the growth rate of green technology innovation showed a slowdown in 2021. Notably, there are disparities in the coupling coordination degree among cities, with economically developed areas exhibiting a faster growth rate. Moreover, green technology innovation significantly enhances carbon emission performance, and heterogeneity tests indicate that this impact is even more pronounced in cities with weaker environmental regulations. Despite regional differences, the overall trend remains positive.

Multi-Scale Evaluation and Simulation of Livelihood Efficiency in Post-Poverty Mountainous Areas

Promoting the coordination of livelihoods at the county and farmers’ scales is essential for achieving balanced regional development and rural revitalization in post-poverty mountainous areas. Existing studies predominantly focus on farmers’ or regional livelihood capital and livelihood efficiency at a single scale, lacking research on cross-scale coordination between farmers’ and county livelihoods. Consequently, these studies fail to reveal the interactions and synergistic enhancement pathways between the two scales. This study, using the Qinba mountains in southern Shaanxi as a case, employs system dynamics to construct a coupled system dynamics model of farmers’ livelihood efficiency and county livelihood efficiency. From the perspective of livelihood capital, five regulatory modes, comprising a total of 17 scenarios, were designed and simulated. The results indicate the following data: (1) The coupling coordination degree between farmers’ livelihood efficiency and county livelihood efficiency in the Qinba mountains is 0.623, indicating a moderate level of coordination overall. However, the coupling coordination relationship requires further optimization and adjustment. Specifically, Foping exhibits a severe imbalance, while the coupling coordination degree of Shiquan, Zhashui, Baihe, Pingli, and Lan’gao is in a state of basic coordination. Additionally, 19 other counties, including Lueyang, Ningqiang, Yang, and others, exhibit moderate coordination. (2) Enhancing social or financial capital through various means typically promotes the coordinated development of farmers’ and county livelihood efficiency. On average, social capital and financial capital regulation models can increase the coupling coordination degree by 0.08 and 0.17, respectively. Additionally, strategies such as increasing fixed asset investment and regulating other capital types, including reducing arable land, also effectively improve the coupling coordination degree of farmers’ and county livelihood efficiency. This study provides a decision-making basis for improving the coordination of farmers’ and county livelihoods in post-poverty mountainous areas, thereby promoting economic development and intensive resource utilization. It assists in formulating more precise policy measures and offers a reference for sustainable development and rural revitalization in similar regions.

The Coupling Coordination Relationship and Driving Factors of the Digital Economy and High-Quality Development of Rural Tourism: Insights from Chinese Experience Data

Globally, rural tourism development faces challenges such as inadequate infrastructure, insufficient marketing resources, and unreliable service quality, all of which limit its potential. However, digital technology offers unprecedented opportunities to address these barriers. China’s experience in integrating digital technology into rural tourism provides a valuable case study for understanding the digitalization of rural tourism. This study constructs an index system to assess the coupling coordination relationship between the digital economy and the high-quality development of rural tourism (HQDRT). By employing methods such as the entropy method, coupling coordination degree model, obstacle factor model, and geographic detector, the study examines the evolution of this coupling coordination relationship and its driving mechanisms across 31 provinces (including regions and municipalities) in China from 2012 to 2021. The findings reveal that (1) The development of the digital economy generally lags behind that of the rural tourism, but the coupling coordination relationship between the two is steadily improving. (2) The level of coupling coordination increases from west to east, with spatial distribution patterns evolving from ‘antagonism’ to ‘adaptation’ and then to ‘coordination’ as they move eastward. Most provinces belong to the ‘adaptation’ type. (3) From a nationwide perspective, the primary obstacles impeding the development of the digital economy include an insufficient internet penetration rate, which consequently leads to underdeveloped internet finance development and telecommunications industry development. The major barriers to the HQDRT stem from an inadequate number of tourists and a lack of physical infrastructure. (4) Population density, consumer spending, and R&amp;D are significant drivers of the coupling coordination relationship, with the interaction between urbanization rates and other factors generally weakening the degree of coupling.

Whole-brain modular dynamics at rest predict sensorimotor learning performance

Abstract Neural measures that predict cognitive performance are informative about the mechanisms underlying cognitive phenomena, with diagnostic potential for neuropathologies with cognitive symptoms. Among such markers, the modularity (subnetwork composition) of whole-brain functional networks is especially promising, due to its longstanding theoretical foundations and recent success in predicting clinical outcomes. We used functional magnetic resonance imaging to identify whole-brain modules at rest, calculating metrics of their spatio-temporal dynamics before and after a sensorimotor learning task on which fast learning is widely believed to be supported by a cognitive strategy. We found that participants’ learning performance was predicted by the degree of coordination of modular reconfiguration, and the strength of recruitment and integration of networks derived during the task itself. Our findings identify these whole-brain metrics as promising network-based markers of cognition, with relevance to basic neuroscience and the potential for clinical application.

Ecological Environment Assessment System in River–Riparian Areas Based on a Protocol for Hydromorphological Quality Evaluation

This paper aims to propose a method for the evaluation of the hydromorphological quality of a river and its riparian areas using three essential components: morphological characterization, river connectivity, and vegetation coverage. The method has been applied to the Tordera river in Catalonia, Spain. The general goal is to establish a riparian environment assessment tool by proposing parameters for each of the three mentioned aspects. This approach relies on data collection and evaluation with a simple computational procedure for eliminating subjectivity in the weighting and classification of evaluation levels. In the proposed methodology, the weights of the indicators are determined by the Distance Correlation-Based CRITIC (D-CRITIC) method, and the results are integrated using the Coupling Coordination Degree Model (CCDM). The proposed methodology quantifies assessment parameters and analyzes the environmental problems faced by riparian zones and rivers through the parameters and the results of the CCDM and thus can be used as a basis for proposing methods to improve the ecological situation. The results can be used for the enhancement of the coordination between the development of riparian resources and the requirements of ecosystem protection and utilization, and they can be used to promote the healthy development of ecological environments and the effective use of riparian resources.

Regional Coexistence in the Digital Era: Spatial–Temporal Evolution and Sustainable Strategies of the Coupled System in the Yangtze River Basin, China

Against the backdrop of globalization and ecological civilization, this study aims to analyze the patterns of system coupling coordination development in the Yangtze River Basin under the interacting influences of population growth, ecological conservation, energy utilization, and digital economic development. Using a multisource model, this paper explores the state of coordinated development, spatial–temporal evolution characteristics, and influencing factors in the Yangtze River Basin from 2011 to 2020. The results indicate the following: (1) The overall degree of coupling coordination in the Yangtze River Basin shows better performances in the eastern coastal areas compared to the central and western regions. Over time, the spatial autocorrelation of coupling and coordination increases, exhibiting a significant spatial clustering trend. (2) The Moran’s I index increased from 0.327 to 0.370, with high–high clusters primarily distributed in economically developed coastal provinces, while low–low clusters were observed in remote provinces in the central and western regions, revealing regional development imbalance issues. (3) The driving force analysis shows that green coverage and GDP are the core factors influencing the spatial differentiation of coupling coordinated development. Factors such as the urbanization rate, nighttime light index, and energy consumption had significant impacts in certain years but are generally considered minor factors. The results of this study not only contribute to understanding the dynamic mechanisms of regional coupling and development but also provide a scientific basis for formulating regional coordinated development policies, promoting the achievement of win–win goals of economic growth and ecological civilization in the Yangtze River Basin and similar regions.

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.

Study on the Coupling Coordination Degree and Driving Mechanism of “Production-Living-Ecological” Space in Ecologically Fragile Areas: A Case Study of the Turpan–Hami Basin

One of the key conditions for achieving superior regional growth is ensuring the harmonious development of both the layout and functions of territorial space. Territorial space, which includes production space, living space, and ecological space, serves as a critical system and venue for economic, cultural, and social activities in a region. The harmonized growth of production–living–ecological space (PLES) is essential for attaining sustainable development goals. Research on PLES offers a fresh perspective on promoting sustainable development of the spatial domain and the sustainable use of resources. However, studies on PLE functions in ecologically fragile areas are lacking. Therefore, in this study, which adopts a PLES perspective, land-use data are used to classify land according to the dominant functions of production, ecology, and living. Integration of point-of-interest (POI) data with socio-economic data was established to spatially describe indicators at the grid level and create a scoring system for PLES indicators in ecologically fragile areas. Finally, the entropy weight method, holistic assessment methods, coupling coordination degree model (CCDM), and geodetector were employed to explore the coupling coordination relationships and factors influencing PLESs in the Turpan–Hami Basin from 2010 to 2020. The results indicate that the Turpan–Hami Basin consists predominantly of potential ecological space, mainly in the central and northern regions, which are characterized by the Gobi Desert and bare rock landforms. Over the past decade, the PLES framework has seen a notable rise in the allocation of residential and ecological areas, whereas the portion dedicated to production spaces has diminished. The overall coupling coordination degree (CCD) of PLES in the Turpan–Hami Basin is at a coordinated level and gradually increasing. The most significant impact on the degree of PLES coupling coordination is exerted by population and natural factors. The research findings provide theoretical support for the sustainable utilization of resources in the Turpan–Hami Basin and other ecologically fragile areas while also offering scientific evidence to promote the coupling coordination of PLES, thereby contributing to high-quality regional development.