Search Results (19)

Cropland abandonment (CA) has become a significant threat to agricultural sustainability, particularly in metropolitan suburbs where urban expansion and cropland preservation often conflict. This study examines the Chengdu Directly Administered Zone of the Tianfu New Area in Sichuan Province, China, as a case study, utilizing high-precision vector data from China’s 2019–2023 National Land Survey to identify abandoned croplands through land use change trajectory analysis. By integrating kernel density estimation, spatial autocorrelation analysis, and geographically weighted regression modeling, we quantitatively analyzed the spatiotemporal patterns of CA and the spatial heterogeneity of driving factors in the study area. The results demonstrate an average annual abandonment rate of approximately 8%, exhibiting minor fluctuations but significant spatial clustering characteristics, with abandonment hotspots concentrated in peri-urban areas that gradually expanded toward urban cores over time, while exurban regions showed lower abandonment rates. Cropland quality and the aggregation index were identified as key restraining factors, whereas increasing slope and land development intensity were found to elevate abandonment risks. Notably, distance to roads displayed a negative effect, contrary to conventional understanding, revealing that policy feedback mechanisms induced by anticipated land expropriation along transportation corridors serve as important drivers of suburban abandonment. This study provides a scientific basis for optimizing resilient urban–rural land allocation, curbing speculative abandonment, and exploring integrated “agriculture + ecology + cultural tourism” utilization models for abandoned lands. The findings offer valuable insights for balancing food security and sustainable development in rapidly urbanizing regions worldwide, particularly providing empirical references for developing countries addressing the dilemma between urban expansion and cropland preservation. Full article

Ride-hailing services have reshaped urban commuting patterns, yet the spatiotemporal mechanisms linking built environment features to ride-hailing demand remain underexplored. Existing studies often overlook the joint effects of origin–destination visual walkability. This study integrates ride-hailing GPS trajectories and geospatial data to quantify mobility patterns and built-environment indicators in Chengdu, China. A dual analytical framework combining global regression and localized modeling was applied to disentangle spatial–temporal influences of urban form and socioeconomic factors. The results reveal that population density, floor–area ratio, and housing prices positively correlate with demand, while road density and distance to city center exhibit negative associations. Visual walkability metrics show divergent effects: psychological greenery and pavement visibility reduce ride-hailing usage, whereas outdoor enclosure enhances it. Temporal analysis identifies time-dependent impacts of built environment variables on main urban area travel. Housing price effects demonstrate spatial globality, while population density and city-center proximity exhibit geographically bounded correlations. Notably, improved visual walkability in specific zones reduces reliance on ride-hailing by facilitating sustainable alternatives. These findings provide empirical support for optimizing urban infrastructure and land-use policies to promote equitable mobility systems. The proposed methodology offers a replicable framework for assessing transportation–land-use interactions, informing targeted interventions to achieve metropolitan sustainability goals through coordinated spatial planning and pedestrian-centric design. Full article

Constructing regional ecological security patterns (ESP) and enhancing carbon sequestration are essential for achieving China’s dual-carbon goals. However, rapid urbanization has intensified landscape fragmentation, disrupted ecosystem flows, and significantly altered urban ecological networks, weakening their carbon sink functions. Using the Chengdu metropolitan area (CMA) as a case study, a time-series ESP from 2000 to 2020 was constructed. Morphological Spatial Pattern Analysis (MSPA), the Minimum Cumulative Resistance (MCR) model, the gravity model, and complex network theory were employed to assess the spatiotemporal evolution and carbon sequestration capacity of the ecological network. Results revealed continuous declines in ecological sources and corridors, an initial rise then stabilization in resistance, and weakening connectivity, particularly in central and western subregions. Reductions in modularity and topological indices reflected lower ecological stability and greater vulnerability. Forest land served as the primary carbon sink, closely associated with multiple topological metrics; grassland sequestration correlated with clustering, while water bodies were positively linked to centrality measures. Adding 10 stepping-stone nodes and 45 corridors could enhance carbon sequestration by approximately 4156 Mg C yr⁻¹, with forests contributing 94.8% by 2020. This study provides scientific support for resilient regional ESP construction and dual-carbon strategy advancement. Full article

Human activities exert considerable influence on ecosystem health, a cornerstone for fostering sustainable regional growth, largely through their effects on land use transformations. This study integrates a system dynamics (SD) model with the patch-generating land use simulation (PLUS) model and the VORS (vigor–organization–resilience–ecosystem services) model to simulate the spatiotemporal dynamics of land use/cover change (LUCC) and assess ecosystem health in the Chengdu Metropolitan Area (CMA) from 2020 to 2035. These projections were conducted under three distinct scenarios: the ecological protection scenario (EPS), the natural development scenario (NDS), and the economic development scenario (EDS). The findings indicate the following: (1) Under EPS, NDS, and EDS, both cultivated land and grassland areas decline, and construction land expands by 40.68%, 54.76%, and 75.01%, respectively. (2) Across all three scenarios, ecosystem health demonstrates improvement, and it shifts from “poor” to “moderate.” (3) Ecosystem health levels in the CMA demonstrate significant spatial heterogeneity; they exhibit “low” levels in the central city, while generally stable levels are observed throughout the surrounding region. These results offer a strong scientific foundation for cultivating sustainable land management strategies and protecting ecosystem health in the CMA. Full article

The mobility and openness of smart cities characterize them as particularly complex networks, necessitating the resilience enhancement of smart city regions from a network structure perspective. Taking the Chengdu–Chongqing urban agglomeration as a case study, this research constructs economic, information, population, and technological intercity networks based on the complex network theory and gravity model to evaluate their spatial structure and resilience over five years. The main conclusions are as follows: (1) subnetworks exhibit a ‘core/periphery’ structure with a significant evolution trend, particularly the metropolitan area integration degree of capital cities has significantly improved; (2) the technology network is the most resilient but was the most affected by COVID-19, while the population and information networks are the least resilient, resulting from poor hierarchy, disassortativity, and agglomeration; (3) network resilience can be improved through system optimization and node enhancement. System optimization should focus more on improving the coordinated development of population, information, and technology networks due to their low synergistic level of resilience, while node optimization should adjust strategies according to the dominance, redundancy, and network role of nodes. This study provides a reference framework to assess the resilience of smart cities, and the assessment results and enhancement strategies can provide valuable regional planning information for resilience building in smart city regions. Full article

Ensuring the harmonization between urbanization and water environment systems is imperative for fostering sustainable regional development in the future. With urban agglomerations and metropolitan areas increasingly dominating urbanization trends in China, it is crucial to explore the interdependent relationship between urbanization and the water environment. Such exploration holds significant implications for water resource management and the formulation of urbanization policies. This study utilizes a comprehensive index system encompassing urbanization and the water environment. It examines the coupled and coordinated spatial and temporal dynamics of these systems within the Chengdu-Chongqing Urban Agglomeration from 2011 to 2019. This analysis employs the Coupled Coordination Degree model alongside the spatial autocorrelation model. The results show that there is still much room for improving the urbanization development level and the water environment quality. During the study period, a nonlinear and nearly U-shaped evolutionary trajectory was observed between the two systems. The results suggest that there is a progression from basic to more advanced coordination between urbanization and water environment at the city cluster scale. Urbanization appears to generally lag behind the water environment in terms of coordination. At the municipal scale, there is a gradient in which some cities show better coordination compared to others. Spatially, the coupling and coordination of this region exhibited dual-core development characteristics centered around Chengdu and Chongqing. The region is in the transition stage towards a core-type networked and decentralized development mode, which has not yet formed an integrated pattern. This offers a theoretical and technical framework for harmonizing water environments and urbanization in similar regions globally. Full article

The degradation of urban ecology, particularly in metropolitan areas distinguished by dense populations and impervious surfaces, presents a worldwide challenge linked to swift urban expansion. Despite extensive documentation of urbanization’s impact on broad regions or specific urban ecosystems over defined time periods, there remains a scarcity of studies investigating the spatiotemporal dynamics of landscape pattern (LP) changes in specific ecosystems at small-to-medium scales within inland megacities as a response to urbanization. Therefore, this work focused on the Bailuwan Wetland Park (BWP) in Chengdu, an inland megacity in southwestern China. Employing satellite imagery data from selected years spanning the previous decade (2010–2021, encompassing 2010, 2012, 2015, 2018, and 2021), this investigation delved into the influences of urbanization on the LP over various time-frames and across different land use/land cover (LULC) types. Our study revealed that urbanization has a significant impact on the patch-/landscape-level characteristics, including the class area (CA), number of patches (NP), patch density (PD), percentage of landscape (PLAND), aggregation index (AI), contagion index (CONTAG), largest patch index (LPI), landscape shape index (LSI), fractal dimension index (FRAC_MN), Shannon’s diversity (SHDI), and evenness index (SHEI). Over the period from 2010 to 2021, NP and PD experienced notable increases, while landscape shape (LSI/FRAC_MN) exhibited greater complexity and fragmentation (PLAND) intensified. Further, landscape heterogeneity (AI/CONTAG) and diversity (SHDI/SHEI) decreased. Particularly significant was the conversion of 52 ha of agricultural land to vegetation, resulting in heightened complexity and fragmentation in vegetation patterns. Additionally, the CA of lakes and rivers decreased following the establishment of the park, while the CA and NP of bare land presented significant increases. These findings suggest that rapid urbanization significantly influences the spatial–temporal dynamics of wetland landscape patterns. Consequently, it is imperative for society to prioritize the restoration and protection of urban constructed wetlands. Full article

China’s urban–rural dichotomy has resulted in a widening gap between urban and rural areas, posing significant challenges to rural development. This study aims to investigate the spatio-temporal differentiation and driving mechanisms of rural industry integration within the Chengdu–Chongqing Economic Circle in China. Using panel data from 2011 to 2020, we employed the entropy weight TOPSIS method to construct a comprehensive index that charts the evolution of rural industry integration across various districts and counties. Additionally, we utilized fixed-effect and spatio-temporally weighted regression models to analyze the underlying driving forces behind this integration. Our findings reveal a dynamic and varied landscape of rural industry integration, with different levels of depth and breadth across various subsystems. Spatially, we observed a transition from a dispersed to a more concentrated agglomeration pattern within the Chengdu–Chongqing Economic Circle. This shift suggests a diffusion effect emanating from core metropolitan areas, as well as an attracting force exerted by adjacent metropolitan circles. In terms of drivers, market demand, openness level, financial development, policy support, and agricultural insurance breadth significantly contribute to rural industry integration. However, technological progress and rural human capital exhibit a weaker correlation. Notably, our models identified pronounced spatial–temporal heterogeneity among these influencing factors, highlighting a nuanced and dynamic relationship between them. Overall, our study emphasizes the crucial role of rural industry integration in bridging the urban–rural divide and fostering sustainable agricultural development and rural revitalization. The insights gained from this research provide valuable guidance for policymakers and stakeholders seeking to optimize rural development strategies and unlock the potential of integrated rural industries. Full article

The global ecological decline resulting from urban development presents a significant challenge for numerous regions striving to reconcile conservation efforts with developmental needs. This study explores the relationship between ecosystem service value (ESV) and habitat quality (HQ) under various scenarios to elucidate prospective development trajectories. This study utilized the PLUS model to simulate land use patterns in the Chengdu metropolitan area across four distinct development scenarios. Furthermore, it employed the equivalent factor method and the Invest model to quantify ESV and HQ values, and investigated the coupling coordination between ESV and HQ for each city using a coupling coordination model (CCM). The findings are as follows: (1) Between 2000 and 2020, land use in the Chengdu metropolitan area primarily expanded through the development of construction land. (2) Concurrently, ESV demonstrated a fluctuating trend characterized by an initial decline succeeded by an upsurge, culminating under the Development–Ecological Balance Scenario. Likewise, HQ displayed a similar fluctuating pattern with an initial decline succeeded by an increase, reaching its zenith under the Ecological Dominance Scenario. (3) The coupling coordination between ESV and HQ exhibited variability across cities and scenarios. Ultimately, this study offers a distinctive perspective on evaluating the interplay between urban development and conservation, providing valuable insights for promoting sustainable development in other regions. Full article

The ongoing urban spatial transformation contributes to a more intricate and varied spatiotemporal correlation pattern between metropolitan expansion and the migrant population. In this study, the coupled coordination model (CCD) is applied to enable the quantification of the spatiotemporal correlation index of metropolitan expansion and migrant population from 2010 to 2020. Moreover, various correlation patterns are identified in this research, and the multiscale geographical weighted regression model (MGWR) is employed to examine the spatiotemporal heterogeneity of the influencing factors that contribute to this correlation. The research findings reveal the following insights: (1) The built-up areas increased twofold between 2010 and 2020, with an evident tendency toward southward expansion. In addition, population migration indicates slow migration in the inner metropolitan area and accelerated migration in the outer metropolitan area. The correlation between metropolitan expansion and migrant population follows a central–peripheral layer pattern that is characterized by a low-high-low progression. (2) While the balanced development of public services has somewhat decreased the differentiation patterns observed, the adjustments made to economic growth, employment, and residential markets have intensified the differentiation of spatiotemporal correlation characteristics between the metropolitan expansion and migrant population. (3) This study demonstrates that the Chengdu metropolitan area is transitioning from a rapid development stage driven by structuralism to a human-oriented new urbanization stage. This shift is evident through the clear stage pattern and central–peripheral layer features observed. Through the scientific planning of industry and public service layouts, the promotion of integration employment, residential markets, and the facilitation of urban–rural transformation can be achieved. Implementing these strategies can elevate the standard of human-oriented urban spatial governance, achieve coordinated and balanced development between built-up and residential spaces, and advance the high-quality, sustainable, and inclusive development of metropolitan areas. Full article

Rapid urbanization in China has led to an exponential increase in the stocks of metals used in cities. Exploring their amount and growth patterns is an important way to forecast future metal demand and identify the potential for urban mining. Here, we use a combination of bottom-up and GIS tools to estimate the amount of in-use stocks and scrap metal of steel, copper, and aluminum in 366 regions of mainland China from 2010 to 2020. We then downscaled the 2020 metal scrap volume based on a multi-source dataset of socioeconomic factors. Finally, the accessibility of the urban mining pilot base (UMPB) was calculated using the two-step floating catchment area method (2SFCA), and the spatial layout assessment analysis of the UMPB was conducted under the supply–demand balance perspective. The results showed that the total in-use stocks of steel, copper, and aluminum increased from an initial 3186 million tons to 5216 million tons, with a corresponding trend of continued growth in the amount of metal scrap. The high value of scrap metal in 2020 is concentrated in the Beijing–Tianjin–Hebei urban agglomeration, the Yangtze River Delta region, and the Chengdu–Chongqing metropolitan area. The accessibility results show that the road network distance-based accessibility covered a smaller area than the Euclidean distance-based accessibility, but when the UMPB service radius was set to 300 km, the road network distance-based accessibility could also cover most of the eastern part of China. The spatial evaluation results of UMPB show that for service radii of 200 km and 300 km, low-supply and high-demand areas account for 6.32 percent and 5.89 percent, respectively. Full article

In order to support the green and low-carbon transformation of China’s construction industry and accomplish the dual carbon objective, it is vital to accelerate green technology innovation. Therefore, this paper takes the Chengdu–Chongqing urban agglomeration of China as the study area, using the super-efficiency slacks-based measure (SBM)model and the gravity model to assess the efficiency of green technology innovation in the construction industry, utilizing geographical detectors to investigate the drivers of green technology innovation in the construction industry further. Additionally, we consider each influencing factor’s level of impact on the efficiency of green technology innovation in the construction sector both under the single factor and double factor scenarios. The findings indicate that there is a considerable difference in the efficiency of green technology innovation in the Chengdu–Chongqing metropolitan agglomeration’s construction industry, and the trend is upward. In addition, the research area exhibited spatially heterogeneous characteristics in terms of the efficiency of green technology innovation in the construction industry, and the spatial spillover effect was significantly limited by distance. Further research revealed that environmental legislation, economic development, public environmental concern, urbanization level, and foreign direct investment were the primary driving factors of green technology innovation efficiency in the construction sector, and industrial size was the potential driving factor. The spatial and temporal differentiation of the green technology innovation efficiency in the construction industry was also more affected by the interaction between the dominating factor and the prospective factor than by either factor acting alone. The research’s findings are useful in advancing the green and low-carbon transformation of the construction sector in the Chengdu–Chongqing metropolitan agglomeration by offering theoretical support and decision-making reference. Full article

Previous studies lacked attention to the spatial heterogeneity of the impact of urbanization on carbon emissions. To fill this knowledge gap, this study analyzed the spatio-temporal variations of carbon emissions (TCE), the per capita carbon intensity (PCI), and the economic carbon intensity (ECI) in the Chengdu-Chongqing urban agglomeration (CUA) based on the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) from 2000–2018. Bivariate spatial autocorrelation, and spatial Durbin models were combined to quantify the spatial correlation and driving mechanisms between carbon emission intensity and multi-dimensional urbanization (population, economic, and land urbanization). The following are the main results: (1) The TCE in CUA increased by 3.918 million tons at an average annual growth of 6.86%; CUA ranked last among China’s national strategic urban agglomerations in terms of TCE, PCI, and ECI. (2) High carbon emission values were concentrated in the Chengdu and Chongqing metropolitan areas, presenting a spatial feature of “Core-Periphery” gradient decay. (3) Nearly 30% of the agglomeration had carbon emission growth at low rates, with the growth cores concentrated in the main urban areas of Chengdu and Chongqing. (4) The “Low-Low” positive correlation was the main correlation type between multi-dimensional urbanization and carbon emissions and was distributed mainly in mountainous areas (e.g., Leshan and Ya’an). (5) Among the urbanization dimensions, the impacts on carbon emissions in local and adjacent areas exhibited varying levels of spatial heterogeneity. Economic urbanization was found to have the strongest positive direct and spillover effects; land urbanization inhibited the growth of carbon emissions in local and adjacent areas; population urbanization promoted carbon emission reduction in adjacent areas. Our findings provide support for CUA to carry out cross-city joint governance strategies of carbon emissions, also proving that regional carbon emission reduction should be an integration of various efforts including low-carbon living of residents, green transformation of economy and optimal land management. Full article

The Chengdu Metropolitan Area, located on the eastern edge of the world’s highest plateau, has experienced a period of integrating urban and rural area development for decades. With rapid urbanization and population growth, the vulnerability and security of the ecological environment have become critical aspects to consider in sustainability. Moreover, the presence of different levels of vitality in the study area has a crucial impact on land-use change. Hence, we propose a growth boundary study based on the theory of urban vitality and ecological networks. We focus on identifying the inefficient urban land and urban development potential land, explore their expansion probabilities to conduct spatial simulations for the next 15 years, and combine the ecological network to form a reasonable spatial pattern. Results showed that the proposed model could simulate the urban growth state more accurately within a certain space scale and integrate different limits and influences to simulate different growth strategies under multiple planning periods. Thus, the proposed model can be an effective decision support tool for the government. Full article

Cultivated land is the principal land source for urban expansion. Recent large-scale urban expansion through the occupation of cultivated land has influenced regional food security and the realization of sustainable development goals. Based on data regarding the cultivated land occupied for urban construction in the Chengdu metropolitan area from 2000 to 2018, the spatio-temporal evolution of cultivated land occupied by urban expansion was analysed using the contribution index. Based on a model comparison, the geographically weighted regression (GWR) model was used to explore the spatio-temporal pattern and evolution path of significant driving factors. The results demonstrate that (1) the total area of cultivated land occupied by urban expansion from 2000 to 2018 was 470.528 km² and mainly concentrated in the main urban area of Chengdu City and its surrounding districts and counties. The K value continued to decline from 93.23 to 37.48, indicating that the contribution of cultivated land in urban expansion is decreasing. (2) The GWR model, with a better fitting effect, demonstrates that the significant factors that influence the cultivated land occupied by urban expansion in the study area gradually shift from population aggregation factors to food safety and the proportion of non-farming population. (3) The evolution type of the driving force is mainly dominated by continuous change, and there is significant spatial heterogeneity in the evolution path. The population density → proportion of non-farm population → grain yield → comprehensive and proportion of cultivated land → per capita fixed asset investment → comprehensive → proportion of non-farm population were typical pathways. (4) Realizing the coordination between urban system structural optimization and cultivated land protection policies in the Chengdu metropolitan area is an important way to guarantee regional food and ecological security and promote the green and high-quality development of the metropolitan area. This study can promote coordination between urban expansion and cultivated land protection in metropolitan areas and provide a reference basis for sustainable economic and social development. Full article