Search Results (81)

Using truck GPS trajectory data, this study measures the intensity of economic spatial linkages in Hubei Province at both administrative and cross-administrative scales and examines the hierarchical structure and spatial pattern of its urban economic network. By comparing the results with existing regional plans, the study provides empirical support for regional coordination and spatial planning. Network centrality analysis, linkage intensity measurement, and community detection algorithms are integrated to construct a topological model of the urban economic network from three dimensions: urban node hierarchy, inter-city linkage intensity, and urban cluster structure. To overcome administrative boundary constraints, a 5 km × 5 km grid-based approach is applied to identify functionally connected urban economic communities. The results indicate that Hubei Province’s urban economic network exhibits a highly dominant core accompanied by multiple secondary supporting centers. While the Wuhan Metropolitan Area demonstrates high economic activity, internal horizontal linkages remain relatively weak, and the roles of Yichang and Xiangyang as regional sub-centers require further strengthening. Grid-based analysis further reveals pronounced cross-administrative economic linkages. Accordingly, this study suggests strengthening support for regional sub-centers and promoting better alignment between administrative space and functional space within the spatial planning system, with enhanced cross-regional coordination. Full article

The uneven spatial distribution of data elements poses challenges to regional equity and sustainable development. To unmask spatial dynamics obscured by traditional macro-divisions, this study evaluates data element development across China’s Eight Comprehensive Economic Regions from 2013 to 2022. Using the entropy weight method, Dagum Gini coefficient, Kernel Density Estimation, and spatial autocorrelation models, the results indicate that while the overall development index exhibits a sustained upward trend, inter-regional differences remain the dominant source of spatial inequality. This disparity is primarily driven by the persistent gap between advanced coastal and lagging inland regions. Notably, spatial trajectories diverge significantly: the Eastern Coastal region exhibits coordinated integration, whereas severe internal polarization appears in the Middle Reaches of the Yellow River and the Southwest. Furthermore, the spatial spillover of data elements remains bounded by physical geography. By highlighting these meso-level structural fault lines, this study provides precise empirical evidence for formulating targeted, basin-specific interventions to bridge the digital divide. Full article

Rapid urbanization is reshaping thermal environments worldwide, with the strongest impacts occurring at the interface between urban and non-urban areas. Impervious surfaces, as key indicators of urban expansion, are critical for monitoring urban growth and assessing surface urban heat island (SUHI) effects. Land use and land cover change (LULCC) provides an essential link between urban dynamics and their environmental and societal consequences. Here, we integrated the U.S. Geological Survey (USGS) Climate Global Issues (CGI) Land Cover Product with Landsat thermal time-series to investigate SUHI evolution in two contrasting metropolitan regions: Wuhan, China, and Brasília, Brazil. Using data spanning 1986–2023, we analyzed the relationships between land cover, Landsat-based land surface temperature (LST), and SUHI intensity, and identified persistent thermal hotspots. Results demonstrate that the land cover data utilized increases the accuracy of impervious surface mapping along urban–rural gradients. Average SUHI intensities were 3.4 °C in Wuhan and 3.3 °C in Brasília, with statistically significant warming trends of 0.04 °C/year and 0.01 °C/year, respectively. Maximum temperature proved to be a robust indicator of SUHI intensification, capturing long-term upward trends. Our findings highlight the important role of urban land cover dynamics in shaping temporal SUHI variability and hotspot emergence. This prototype framework demonstrates the scientific and policy value of combining long-term land cover monitoring information with satellite thermal monitoring to quantify and track SUHI at city scale, supporting sustainable urban planning and climate adaptation strategies. Full article

Environmental degradation from rapid urbanization significantly threatens ecological resilience (ER). Nevertheless, accurately evaluating ER remains a persistent challenge. Prior studies’ limited attention to resilience’s cross-scale complexity has hindered evidence-based management. This study, based on long-term time series remote sensing and multi-source data, developed a cross-scale spatiotemporal ER analysis framework integrating landscape ecology and panarchy perspectives. A local “resistance–adaptation–recovery” substrate resilience evaluation was combined with telecoupling-based global network resilience to quantify multi-scale ER from 2000 to 2020. Key drivers across time scales were identified using a hybrid XGBoost–SHAP and genetic algorithm (GA)–optimized dynamic Bayesian network (DBN), and spatial optimization scenarios were simulated with patch-generating land use simulation (PLUS) model. ER decreased slightly from 0.4856 in 2000 to 0.4503 in 2020, with dynamic fluctuations across periods. A clear spatial pattern emerged, with higher ER in the east and lower in the west. Forest land contributed strongly to ER, while construction and cropland reduced it. Spatial composition factors—especially the proportions of forest and construction land—were dominant drivers, outweighing structural factors such as landscape pattern. DBN backward inference revealed nonlinear threshold effects among socio–natural–spatial drivers. Scenario-based simulations confirmed that regulating spatial composition via our optimization pathway can enhance ER. This is particularly effective when expanding forestland in mountainous regions while restraining the growth of built-up areas. This study proposes an integrated framework of “resilience assessment—driver analysis—spatial optimization,” which not only advances the theoretical basis for nested ER assessment but also offers a transferable approach for optimizing spatial patterns and sustainable land management, thereby enhancing ecological resilience in rapidly urbanizing regions. Full article

Climate change is profoundly reshaping watershed hydrological regimes and threatening the sustainability of regional ecosystems, rendering traditional ecological restoration planning—primarily reliant on static baselines—insufficient to support long-term resilience under future environmental conditions. To enhance the sustainability of metropolitan ecological restoration, this study develops a climate-adaptive restoration framework for the Wuhan Metropolitan Area, structured around “climate scenario—hydrological simulation—zoning delineation—strategy formulation.” The framework aims to elucidate how projected hydrological shifts constrain the spatial configuration of ecological restoration. Under the RCP4.5 (Representative Concentration Pathway 4.5) scenario, the WEP-L (Water and Energy transfer Processes in Large river basins) distributed hydrological model was calibrated and validated using observed hydrological data from 2016–2020 and subsequently applied to simulate the spatiotemporal evolution of precipitation, evapotranspiration, runoff, and total water resources in 2035. Hydrological trend analyses were further conducted at the secondary watershed scale to assess the differentiated impacts of future hydrological changes across planning units. Based on these simulations, ecological sensitivity and ecosystem service assessments were integrated to identify priority restoration areas, forming a “five-zone × three-tier” sustainable restoration zoning system encompassing farmland restoration, forest ecological restoration, soil and water conservation restoration, river and lake wetland ecological restoration, and urban habitat improvement restoration, classified into general, important, and extremely important levels. A comprehensive “four-water” management scheme—addressing water security, water resources, water environment, and water landscape—was subsequently proposed to strengthen the sustainable supply capacity and overall resilience of metropolitan ecosystems. Results indicate that by 2035, hydrological processes in the Wuhan Metropolitan Area will exhibit pronounced spatial heterogeneity, with uneven changes in precipitation and runoff further intensifying disparities in regional water availability. These findings highlight the necessity of incorporating scenario-based hydrological constraints into sustainable ecological restoration planning. The proposed technical framework provides a transferable pathway for enhancing watershed ecosystem sustainability and resilience under climate change. Full article

To address the utilization challenges of rural settlements in metropolitan suburbs, this study takes the suburban areas of Wuhan as its research object. Based on mobile signaling data and multi-source geographic data, it evaluates their utilization efficiency and construction suitability from both dynamic and static dimensions, and proposes zoning optimization strategies. The study constructed a population mobility network, revealing that rural population flow in Wuhan radiates primarily from the main urban core, with net inflow or balance prevalent in near-suburban areas and net outflow dominant in distant suburbs. The results indicate that only 11.45% of villages achieve medium-to-high utilization efficiency, while 94.50% of the area is classified as highly suitable for development. Based on the “Efficiency-Potential” matrix, villages are categorized into five types, including key development type, gradual optimization type, potential activation type, steady-state improvement type and priority exit type. This study contributes to our understanding of the relationship between rural population and land, and provides support for the optimization of suburban settlements and rural revitalization. Full article

Urban expansion intensifies economic–environmental conflicts, making human settlement quality increasingly critical for sustainable development. This study applies ecological niche theory to evaluate the evolution of human settlement quality in the Wuhan Metropolitan Area (WMA) from 2014 to 2022 using 21 economic, social, and ecological indicators. The results reveal: (1) significant variations in niche-fitness values across subsystems, with Wuhan maintaining superiority (>0.820) despite a gradual decline, while peripheral cities—notably Huangshi, Tianmen, and Ezhou—consistently ranked lower (<0.610) throughout the study period; (2) three evolutionary trajectories emerged, characterized by continuous decline, inverted U-shaped development, and sustained growth, reflecting nonlinear dynamics and path dependence in the region’s development patterns. These findings underscore persistent core-periphery disparities within the metropolitan area, yet improved regional coordination is evident as inter-city evaluation gaps narrowed from 0.329 to 0.231 between 2014 and 2022. Based on these insights, tailored policy recommendations are proposed to address the identified disparities and promote balanced development. This study offers valuable theoretical and practical contributions toward achieving coordinated and sustainable development in metropolitan regions. Full article

Environmental policy helps policymakers and researchers understand the process and expected effects of policy before the policies are fully implemented. This study aims to estimate the effects of resource-conserving and environmentally friendly policy implemented in the Wuhan metropolitan area and Changsha–Zhuzhou–Xiangtan urban agglomeration. The synthetic control method is employed as an estimation method. The results show that policy has positive impacts on economic development and SO₂ emission reduction in the pilot regions but cannot improve wastewater treatment. Compared to large cities, medium-sized and small cities are more sensitive to policies since the large cities have transferred a large number of enterprises with high energy consumption and high emissions to the surrounding medium-sized and small cities. The study also finds that the Wuhan metropolitan area reduces pollution emissions through increasing environmental investment and the efficiency of resource allocation. In the Changsha–Zhuzhou–Xiangtan urban agglomeration, policy triggers green technology innovation to improve the environment and boost the economy. Full article

The rapid adoption of electric vehicles (EVs) has driven a strong need for optimizing locations of electric vehicle charging stations (EVCSs). Previous methods for locating EVCSs rely on statistical and optimization models, but these methods have limitations in capturing complex nonlinear relationships and spatial dependencies among factors influencing EVCS locations. To address this research gap and better understand the spatial impacts of urban activities on EVCS placement, this study presents a spatially aware machine learning (SAML) method that combines a multi-layer perceptron (MLP) model with a spatial loss function to optimize EVCS sites. Additionally, the method uses the Shapley additive explanation (SHAP) technique to investigate nonlinear relationships embedded in EVCS placement. Using the city of Wuhan as a case study, the SAML method reveals that parking site (PS), road density (RD), population density (PD), and commercial residential (CR) areas are key factors in determining optimal EVCS sites. The SAML model classifies these grid cells into no EVCS demand (0 EVCS), low EVCS demand (from 1 to 3 EVCSs), and high EVCS demand (4+ EVCSs) classes. The model performs well in predicting EVCS demand. Findings from ablation tests also indicate that the inclusion of spatial correlations in the model’s loss function significantly enhances the model’s performance. Additionally, results from case studies validate that the model is effective in predicting EVCSs in other metropolitan cities. Full article

This study focuses on the Triangle of Central China and investigates the spatiotemporal evolution, driving factors, and impacts of population aging on regional sustainable development from 2000 to 2020. The study adopts an innovative two-scale analytical framework at the prefecture and district/county level, integrating spatial autocorrelation analysis, the Geodetector model, and geographically weighted regression. The results show a significant acceleration in population aging across the study area, accompanied by pronounced spatial clustering, particularly in western Hubei and the Wuhan metropolitan area. Over time, the spatial distribution has evolved from a relatively dispersed pattern to one of high concentration. Key drivers of the spatial heterogeneity of aging include economic disparities, demographic transitions, and the uneven spatial allocation of public services such as healthcare and education. These aging patterns profoundly affect the region’s potential for sustainable development. Accordingly, the study proposes a multi-scale collaborative governance strategy: At the prefecture level, efforts should focus on promoting the coordinated development of the silver economy and optimizing the spatial redistribution of healthcare resources; At the district and county level, priorities should include strengthening infrastructure, curbing the outflow of young labor, and improving access to basic public services. By integrating spatial analysis techniques with sustainable development policy recommendations, this study provides a basis for scientifically measuring, understanding, and managing demographic transitions. This is essential for achieving long-term socioeconomic sustainability in rapidly aging regions. Full article

Establishing a resilient bird habitat network (BHN) and identifying ecological strategic areas for protection are critical for conserving biodiversity and maintaining ecosystem stability in wetland cities. However, existing ecological network studies often overlook dynamic resilience that incorporates explicit species information, and their scenario-based assessments lack systematic evaluation metrics. This study, using Wuhan—an international wetland city—as a case study, integrates Maximum Entropy (MaxEnt), remote sensing ecological index (RSEI) and circuit theory to identify a high-quality BHN. A comprehensive resilience assessment and optimization framework is developed, grounded in structure–function–quality indicators and informed by resilience and complex network theory. Key findings include: (1) The network comprises 147 habitat patches and 284 ecological corridors, demonstrating marked spatial heterogeneity. Habitats are predominantly located in the southern and southwestern regions of Wuhan, concentrated in contiguous green spaces. In contrast, habitats in the urban core are fragmented and small. Corridors are mainly distributed in the southwestern and central metropolitan areas. (2) Under deliberate attack, considering resilience centrality, the network’s resilience declined more slowly than in scenarios based on traditional centrality measures. Across combined node and corridor attack simulations, two critical resilience thresholds were identified at 30% and 50%. (3) The ecological strategic space is primarily composed of key habitat patches (58, 108, 117, and 27) and corridors (119–128, 9–12, 122–147, 128–138, 76–85, and 20–29), mainly located in the southern region of Wuhan, particularly around Liangzi Lake and Anshan National Wetland Park. This study advances a dynamic framework for BHN resilience assessment, planning, and restoration, providing scientific guidance for enhancing ecological security and biodiversity conservation in urban wetland environments. Full article

As a pivotal ecological–economic nexus in China, the Yangtze River Basin (YRB)’s spatiotemporal evolution of habitat quality (HQ) profoundly influences regional sustainable development. This study establishes a tripartite analytical framework integrating remote sensing big data, socioeconomic datasets, and ecological modeling. By coupling the InVEST and PLUS models with Theil–Sen median trend analysis and Mann–Kendall tests, we systematically assessed HQ spatial heterogeneity across the basin during 2000–2020 and projected trends under 2030 scenarios (natural development (S1), cropland protection (S2), and ecological conservation (S3)). Key findings reveal that basin-wide HQ remained stable (0.599–0.606) but exhibited marked spatial disparities, demonstrating a “high-middle reach (0.636–0.649), low upper/lower reach” pattern. Urbanized downstream areas recorded the minimum HQ (0.478–0.515), primarily due to landscape fragmentation from peri-urban expansion and transportation infrastructure. Trend analysis showed that coefficient of variation (CV) values ranged from 0.350 to 2.72 (mean = 0.768), indicating relative stability but significant spatial variability. While 76.98% of areas showed no significant HQ changes, 15.83% experienced declines (3.56% with significant degradation, p < 0.05) concentrated in urban agglomerations (e.g., the Wuhan Metropolitan Area, the Yangtze River Delta). Only 7.18% exhibited an HQ improvement, predominantly in snowmelt-affected Qinghai–Tibet Plateau regions, with merely 0.95% showing a significant enhancement. Multi-scenario projections align with Theil–Sen trends, predicting HQ declines across all scenarios. S3 curbs decline to 0.33% (HQ = 0.597), outperforming S1 (1.07%) and S2 (1.15%). Nevertheless, downstream areas remain high-risk (S3 HQ = 0.476). This study elucidated compound drivers of urbanization, agricultural encroachment, and climate change, proposing a synergistic “zoning regulation–corridor restoration–cross-regional compensation” pathway. These findings provide scientific support for balancing ecological protection and high-quality development in the Yangtze Economic Belt, while offering systematic solutions for the sustainable governance of global mega-basins. Full article

Green technological innovation is pivotal in advancing the ‘dual carbon’ target and promoting sustainable and low-carbon development. This research examines 17 prefecture-level cities in Hubei Province, employing the Super-SBM model for assessing emissions of carbon efficiency from 2010 to 2020. The kernel density estimation and the Dagum coefficient of Gini are also used to examine the spatio-temporal differentiation and the evolution of these efficiencies. A data panel regression model is utilized to evaluate how green technological innovation impacts carbon emission efficiency in Hubei Province. The research revealed that (1) Hubei Province’s carbon emission efficiency first fluctuated and then increased rapidly, and (2) the overall regional difference in carbon emission efficiency in Hubei Province shows a trend of first decreasing and then gradually increasing. The Wuhan metropolitan area and the Xiang-yang-Shiyan-Suizhou-Shennongjia urban area are quite different; the differentiation within the Yichang-Jingzhou-Jing-Enshi urban agglomeration shows a narrowing trend. (3) The innovation elements of green technology are positively correlated with the effectiveness of carbon emissions; the relationship between economic expansion and population density among the control variables also shows a positive correlation, while the industrial structure and government environmental regulations are negatively correlated. (4) In Hubei Province, there is a temporal lag between green technological innovation and its impact on carbon emission efficiency. Capital investment and technical achievement currently enhance carbon emission efficiency, while human capital positively affects carbon emission efficiency during a second lag period. This article proposes countermeasures and recommendations for R&D capital spending, innovative talent cultivation, and regional differentiation, providing specific references to advance the coordinated growth of the whole Hubei Province and green sustainable development. Full article

The development and utilization of urban underground space represents a crucial strategy for achieving sustainable urban development. Three-dimensional (3D) geological models provide a data foundation and technical support for research in urban planning and construction, as well as the prevention and control of environmental geological issues. However, current urban 3D geological modeling generally faces the challenge of multi-source heterogeneous modeling data. This often necessitates varying degrees of generalization in data processing, resulting in the majority of current urban 3D geological models being relatively coarse and insufficient to fulfill the demand for detailed geological information in contemporary urban development and management. Therefore, determining how to formulate or optimize the 3D geological modeling schemes to enhance the utilization of multi-source heterogeneous data is a key challenge in current urban 3D geological modeling. This study, taking the 3D geological structure modeling of Wuhan’s metropolitan development area (MDA) as an example, develops an automated scheme for standardizing modeling data based on multi-scale geological chronostratigraphy. By utilizing the standardized stratigraphy as a unified and independent geological framework for layered modeling, a high-precision 3D geological model of Wuhan’s MDA, characterized by large-scale and ultra-complex geological conditions, is constructed through a methodology that integrates the global discrete constrained points modeling approach with the global layered modeling approach, without generalizing the multi-source heterogeneous modeling data. This research not only holds significant practical implications for the prevention and control of comprehensive urban geological issues in Wuhan but also provides novel technical insights into the methodology of 3D urban geological modeling. Full article

Innovating institutional incentives and promoting multiple-subject interaction and cooperation to create ecological value of cultivated land are practical requirements for the sustainable protection of cultivated land and high-quality development of agriculture and rural areas. We performed a survey questionnaire of 862 farmers in the Wuhan Metropolitan Area and used the fuzzy set qualitative comparative analysis (fsQCA) method to explore the institutional configuration effect of farmers’ behavior in the ecological value co-creation of cultivated land (FBEVCCL). The institutional configuration characteristics of the ecological value co-creation of cultivated land was analyzed, and we propose institutional optimization suggestions for the ecological value co-creation of cultivated land. The research results demonstrated the following: (1) A single institutional element does not constitute a necessary condition for the FBEVCCL, and it is necessary to analyze the institutional configuration effect. (2) Four institutional configurations lead to high-level FBEVCCL. Both formal and informal configurations have important impacts on the FBEVCCL, but the guidance, subsidies, and constraints of formal institutions are often the core driving factors, complemented by the shaping of farmers’ values to jointly enhance the FBEVCCL. The formal institutions of publicity and guidance, rewards and subsidies, and disciplinary constraints can to some extent replace each other. (3) The three institutional configurations lead to low-level FBEVCCL, and the lack of informal and formal institutions for incentives and punishments is the main reason for low-level FBEVCCL. In the future, we should further standardize the reward and punishment mechanism, enhance farmers’ green production skills, and sustainably enhance the behavior of farmers in the ecological value co-creation of cultivated land. Full article