Search Results (98)

The Urban Agglomeration in the Middle Reaches of the Yangtze River (UAMRYR), serving as a pivotal hub for coordinated economic and ecological development in central China, is characterized by marked ecological fragility and climate sensitivity. Investigating the land use dynamics and ecological benefit changes within this region holds critical strategic significance for balancing regional development with the construction of ecological security barriers. This study systematically analyzed the spatiotemporal variations in land use/land cover (LULC) across the UAMRYR, using multi-source remote sensing data, climatic factors, land conditions, and anthropogenic influences. By integrating the four-quadrant model and the coupling degree model, we developed a remote sensing ecological index (RSEI)–ecological service index (ESI) coupling evaluation framework to assess the spatiotemporal evolution patterns of changes in ecological benefits in the region. Furthermore, we employed Geodetector analysis to identify the key influencing factors driving the RSEI–ESI coupling relationship and their interactive mechanisms. The research findings are as follows: (1) The ecological regional pattern has changed. The area of Quadrant I (RSEI > 0.5 and ESI > 0.5) decreased by 13,800 km², whereas Quadrants II (RSEI < 0.5 and ESI > 0.5) and IV (RSEI > 0.5 and ESI < 0.5) increased by 14,900 km² and 3500 km², respectively. Quadrant III (RSEI < 0.5 and ESI < 0.5) remained relatively stable. This indicates that the imbalance in ecological functional spaces has intensified, affecting key ecological processes. (2) The quantitative analysis of the spatiotemporal evolution characteristics of the RSEI and ESI revealed contrasting trends: the RSEI decreased by 0.006, whereas the ESI showed a slight increase of 0.001. (3) The ranking of the driving factors indicated that the Normalized Difference Vegetation Index (NDVI) and the mean annual rainfall (MAP) were the primary factors driving ecological evolution, while the influence of economic driving factors was relatively weak. This study establishes a three-pillar framework (quadrant-based diagnosis, Geodetector-driven analysis, and RSEI–ESI coupled interventions) to guide precision-based ecological restoration and spatial governance. Full article

Urban agglomerations serve as essential platforms for regional innovation, while agricultural technology innovation and diffusion play pivotal roles in enhancing agricultural eco-efficiency (AEE). Based on panel data from the Urban Agglomeration in the Middle Reaches of the Yangtze River (UAMRYR) (2001–2023), this study employs a super-efficiency slacks-based measure model incorporating undesirable outputs to evaluate agricultural eco-efficiency. A modified gravity model is utilized to construct agricultural technology innovation networks (ATINs) in urban agglomerations, and a spatial Durbin model is applied to examine the spillover effects of network structure on eco-efficiency. The results indicate that: (1) Higher-degree centrality within the innovation network significantly improves local agricultural eco-efficiency and produces positive spillover effects on neighboring cities; (2) both direct and spillover effects are significant in central cities, whereas sub-central cities exhibit only a significant direct effect, and peripheral cities display an insignificant direct effect but a significant spillover effect; and (3) enhanced urban informatization, agricultural financial development, and industrial scale substantially strengthen the spatial spillover effects of the innovation network, thereby further advancing agricultural eco-efficiency within the agglomeration. These findings offer theoretical and empirical support for optimizing agricultural technology pathways and enhancing eco-efficiency in urban agglomerations. Full article

The Middle Yangtze River Urban Agglomeration, a critical ecological barrier in China, faces escalating pressures from rapid urbanization and climate change, leading to fragmented landscapes and degraded ecosystem services. To address the synergistic challenges of ecological protection and risk management, this paper takes the urban agglomeration in the middle reaches of the Yangtze River as the study area, and obtains the source patches through morphological spatial pattern analysis. Based on the spatial distribution of risky source areas, ecological blind zones are cut down by optimizing buffer zones and merging fragmented patches. Finally, a composite ecological network is constructed through circuit theory superimposed on the dual network method. The results showed that (1) there are 16 ecological source patches and 16 risk source patches in the study area. Six complementary ecological sources and four new ecological sources were obtained through the blind zone reduction strategy. The percentage of ecological blind zones reduced from 58.4% to 39.5%. (2) The integrated nodes with 11,366 connecting edges were identified. The integrated nodes are distributed around the central Jiuling-Mafushan Mountains, mainly in the western and southern areas of the Dongting Lake Plain. (3) Primary integration nodes are critical for network stability, with a 75% node failure threshold triggering systemic collapse. The proposed strategy of “mountain protection–plain control–railway monitoring” is consistent with China’s territorial and spatial planning. By incorporating the risk network into the conservation framework, this study provides feasible insights for balancing development and sustainability in ecologically fragile areas. Full article

As global urbanization accelerates and economic development progresses rapidly, a series of ecological and environmental challenges have emerged. In certain countries, particularly in developing nations such as China, India, and Bangladesh, flood detention areas (FDAs) have been increasingly encroached upon by urbanization, resulting in growing conflicts between flood control functions and economic development. Therefore, accurately predicting urban expansion trends in these regions is considered essential for providing scientific guidance for sustainable regional development. In this study, the PLUS model was selected as the baseline based on comparative experiments. On this foundation, a novel AIF-HOM-PLUS framework was developed. In this framework, a new method, Adjacent Image Fusion (AIF), was proposed to reduce local temporal noise by utilizing adjacent multi-temporal data. Subsequently, Higher-Order Markov chains (HOM) were incorporated to capture complex temporal dependencies and long-term transition patterns. The Middle-Reach Yangtze River urban agglomeration (MRYRUA), including FDAs in the Yangtze River Basin (YRB), was selected as the study area, and LULCCs in 2035 and 2050 were predicted. The results showed the following: (1) among the basic models, the PLUS model exhibited the best performance, while the AIF method significantly improved its overall accuracy (OA) by 2%; (2) the area of impervious surfaces within the FDAs of the YRB will increase at an average annual rate of 1.29%, which pertains to the conflict between the United Nations Sustainable Development Goals (SDGs) 9.1 and SDG 11.a, which has become a critical issue that needs urgent attention; (3) the area of impervious surfaces in the MRYRUA will increase at an average annual rate of 1.3%, primarily at the expense of cropland and water bodies. 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

This research aimed to investigate whether transformation of the industrial sector in a region could improve industrial land use efficiency. Taking the urban agglomeration in the middle reaches of the Yangtze River in China as the research area, we compiled socioeconomic panel data from 2000 to 2020 in order to analyze the impact of the transformation of industrial sectors in an area on industrial land use efficiency from two dimensions: industrial structural optimization and industrial spatial layout. The research results show the following: (1) The rationalization and upgrading of the industrial sector, as well as the professional agglomeration of industry and diversified industrial agglomeration, have improved the efficiency of industrial land use. (2) The impact of industrial rationalization on industrial land use efficiency presents an inverted U-shaped curve, whereby the impact of industrial upgrading on industrial land use efficiency has a relatively small spatiotemporal heterogeneity. The spatiotemporal changes in the impact of industrial specialized agglomeration on industrial land use efficiency are relatively small, while the spatiotemporal changes in the impact of industrial diversified agglomeration on industrial land use efficiency are more obvious. (3) There is obvious spatial heterogeneity in the two dimensions industrial structural optimization and industrial spatial layout in the three sub-regions when improving industrial land use efficiency. Full article

Regional comprehensive transportation infrastructures constitute the fundamental basis for the development of inland urban agglomerations. To elucidate the role of comprehensive transportation in shaping the spatial organization and expansion of urban agglomerations, this study takes the Yangtze River Middle Reaches Urban Agglomeration (YRMRUA) as a case example. It examines the spatial relationships between transportation network layout and spatial expansion patterns using fractal dimension based on traffic accessibility, traffic-weighted linear density, and Pearson correlation analysis. The key findings of this study are as follows: (1) The YRMRUA exhibits a partial fractal growth pattern influenced by transportation development, which indicates that the comprehensive transportation has a significant but limited impact on YRMRUA. (2) There is a moderate correlation between traffic-weighted linear density and spatial expansion intensity within YRMRUA. (3) Specific groups such as the Wuhan–Ezhou–Huanggang–Huangshi group, Changsha–Zhuzhou–Xiangtan group, and Nanchang–Yichun group have formed in areas where transportation development and spatial expansion are at the forefront. (4) Different modes of transportation, including waterway transportation, railway transportation, and road transportation, have varying effects on spatial expansion. The integration of these modes forms the fundamental framework of urban agglomerations. Full article

The accelerated development of urban agglomerations in China has resulted in the significant regional expansion of infrastructure and urban spaces, which has led to the fragmentation of habitats and the degradation of ecosystem function. Ecological networks have been shown to reconnect isolated habitat patches within urban agglomerations by identifying ecological sources and constructing corridors, which could enhance regional ecological security. Nature reserves, as critical areas for the protection of key species and ecosystems, play a vital role in this process. Investigating the influence of nature reserves on the ecological networks of urban agglomerations helps to integrate regional ecological resources, optimize ecological network structures, and enhance cross-departmental coordination in nature reserve management and ecological environment protection. Using the urban agglomeration in the middle reaches of the Yangtze River as a case study, this research analyzes the impact of nature reserves on the ecological network of urban agglomerations. Initially, ecological source patches are identified using the “Quality-Morphology-Connectivity” evaluation model. Different types of nature reserves are then superimposed to create four distinct source schemes. Subsequently, a resistance surface is constructed through a comprehensive evaluation method to assess ecological barriers. Then, ecological corridors are generated using circuit theory tools. Finally, a comparison of the effectiveness of the four ecological networks is conducted using 12 landscape pattern metrics. The results indicate several key points. Firstly, the inclusion of nature reserves is shown to supplement ecological sources and increase corridor numbers, thereby enhancing the optimization effect of the urban agglomerations’ ecological network threefold. Secondly, the impact of nature reserves on the ecological network is closely related to the spatial scale of patches, and patch scale consistency should be considered to prevent network functionality loss. Thirdly, establishing a cross-departmental and cross-regional collaborative management mechanism is recommended to organically integrate nature reserves with ecological networks. These results provide a data-driven foundation for the optimization of ecological networks in urban agglomerations and inform effective management strategies for nature reserves, to promote the construction of ecological civilization in urban agglomerations. Full article

Spanning China’s eastern, central, and western regions, the Yangtze River Economic Belt (YREB) is a pivotal area for economic growth and carbon emissions, with its three major urban agglomerations serving as key hubs along the upper, middle, and lower reaches of the Yangtze River. Understanding the driving factors of carbon emissions and simulating carbon peak scenarios in these regions are critical for informing low-carbon development strategies across China’s diverse geographical zones. This study employs Grey Relational Analysis to identify key drivers and applies the Logarithmic Mean Divisia Index (LMDI) decomposition method to quantify the contributions of various factors to carbon emissions from 2005 to 2021. Furthermore, the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model is utilized to project future emission trends under multiple scenarios. The results indicate that (1) the growth rate of carbon emissions in the three urban agglomerations has generally decelerated during the study period; (2) the influence of driving factors varies significantly across regions, with economic development, urbanization, and population size positively correlating with carbon emissions, while energy structure and energy intensity exhibit mitigating effects; and (3) tailored emission reduction strategies for each urban agglomeration—namely, the Yangtze River Delta Urban Agglomeration (YRD), the Middle Reaches of the Yangtze River Urban Agglomeration (TCC), and the Chengdu-Chongqing Urban Agglomeration (CCA)—can enable all three to achieve carbon peaking by 2030. These findings provide a robust foundation for region-specific policy-making to support China’s carbon neutrality goals. Full article

New quality productive forces serve as a catalyst for high-quality development and act as a critical driver of Chinese-style modernization. This study evaluated the degree of new quality productive force in China’s five major urban agglomerations between 2013 and 2022 using the entropy approach. Additionally, it utilized kernel density estimation, the Dagum Gini coefficient, and Markov chain analysis to explore the spatial and temporal dynamics of these forces and their evolutionary trends. The findings revealed the following: (1) Overall, the new quality productive forces in China’s five major urban agglomerations have exhibited a steady upward trend, although the overall level remains relatively low. Among these regions, the Pearl River Delta ranks the highest, followed by the Yangtze River Delta, Beijing–Tianjin–Hebei, Chengdu–Chongqing, and the Urban Cluster in the Middle Reaches of the Yangtze River. Nevertheless, significant potential for improvement persists. (2) The traditional Markov probability transfer matrix suggests that the new quality productive forces in these urban agglomerations are relatively stable, with evidence of “club convergence”. Meanwhile, the spatial Markov transfer probability matrix indicates that transfer probabilities are influenced by neighborhood contexts. (3) Over time, the new quality productive forces in Chinese urban agglomerations show a tendency to concentrate at higher levels, reflecting gradual improvement. The developmental state and evolutionary patterns of new quality productive forces in Chinese urban agglomerations are thoroughly evaluated in this paper, along with advice for accelerating their growth to promote Chinese-style modernization. Full article

China’s rapid urbanization has spurred economic growth and posed environmental challenges. We investigate the relationship between multidimensional urbanization and environmental pollution by a fixed effect model based on the panel data of 70 cities in three major urban agglomerations in the Yangtze River Economic Belt during 2005–2020. Overall, environmental pollution aggravates and then decreases in three major urban agglomerations, which is closely related to China’s environmental pollution control policies. Environmental pollution shows obvious spatial heterogeneities by five levels in three major urban agglomerations, which have been gradually changed from high-value levels to low-value levels. In the Yangtze River Economic Belt, environmental pollution is dominated by “High–High” and “Low–Low” clusters. Among them, “High–High” clusters move eastwards, while “Low–Low” clusters gradually concentrate southeastwards. Multidimensional urbanization helps to alleviate regional environmental pollution. Economic, social, and land urbanization reduces environmental pollution in three urban agglomerations to a certain extent. Population urbanization has a non-significant effect on environmental pollution. Social urbanization has improved environmental pollution in the Chengdu–Chongqing urban agglomeration (CC) and the Yangtze River Delta (YRD), which is increased by population urbanization in the middle reaches of the Yangtze River (MYR) and is improved by comprehensive urbanization in CC. Full article

Studying the temporal and spatial variation characteristics and driving factors of carbon reserves in the middle reaches of the Yangtze River urban agglomeration is crucial for achieving sustainable development and regional ecological conservation against the backdrop of the “double carbon” plan. Based on three periods of land use data from 2000 to 2020, combined with the InVEST model(Version 3.14.2), the spatiotemporal changes in carbon storage in the urban agglomeration in the middle reaches of the Yangtze River were analyzed. The PLUS model (Version 1.3.5) was used to predict three scenarios of natural development, urban development, and eco-development in the urban agglomeration in the middle reaches of the Yangtze River in 2035 and estimate the carbon storage of the ecosystems under different scenarios, and it used optimal parameter GeoDetectors (Version 4.4.2) to reveal the driving factors affecting the spatiotemporal differentiation of carbon storage. The results show that farmland and construction land area increased and forestland area continued to decrease from 2000 to 2020. Carbon storage decreased by 1 × 10⁶ t, with forestland conversion to farmland and construction land being the main decreasing drivers. The carbon storage of natural and urban developments decreased by 0.26 × 10⁶ t and 0.32 × 10⁶ t, while it increased by 0.16 × 10⁶ under ecological development. The results of the factor detector showed that the NDVI (Normalized Difference Vegetation Index) had the highest explanatory power on the spatiotemporal variation in carbon storage (q = 0.588), followed by the slope (q = 0.454) and elevation (q = 0.391), and the explanatory power of natural environmental factors on the spatiotemporal variation in of carbon storage was dominant. The interaction detector results showed that the spatiotemporal variation in carbon storage was affected by multiple factors, the interaction intensity between each driving factor was stronger than that of a single factor, and the synergy between the NDVI and slope was the strongest, at q = 0.646. Full article

The Yangtze River Economic Belt (YREB), spanning 11 provinces and municipalities across China, is of paramount importance due to its high economic development and strategic role in national distribution. However, the YREB, which has experienced rapid economic growth, faces challenges resulting from its previously expansive development model, including regional resource and environmental issues. Consequently, a systematic analysis encompassing socio-economic, ecological, and resource-environmental aspects is vital for a comprehensive and quantitative understanding of the YREB’s overall condition. This study explores resource and environmental carrying capacity (RECC) by constructing an integrated framework that includes remote sensing data, geographic information data and social statistical data, which allows for a precise analysis of RECC dynamics from 2010 to 2020. The findings demonstrate an upward trend in the overall quality of RECC from 2010 to 2020, achieving higher grades over time. However, there is significant spatial heterogeneity, with a notable decrease in RECC levels moving from the eastern to the western regions within the YREB. Moreover, low-level RECC areas situated in the northwest of the YREB, show a trend of moving toward regions of higher altitude from 2010 to 2020 based on analysis using the standard deviation ellipse (SDE) method. When considering to the three major urban agglomerations within the YREB, overall RECC in middle and lower agglomerations is generally stable and on an upward trend while cities in upper reaches exhibit significant variation and fluctuations, highlighting them as areas requiring future focus. Therefore, specific indicators were applied to monitor RECC risk for each of these three agglomerations, respectively, after which optimized strategies could be proposed based on different early warning levels. Ultimately this study allows local authorities to implement timely and effective interventions to mitigate risks and promote sustainable development. Full article

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. Full article

China’s accelerating pace of urbanization has placed severe pressure on its ecosystems. Hence, the monitoring and assessment of eco-environmental quality has significant implications for sustainable urban development. By introducing a pollution index, a modified remote sensing ecological index (MRSEI) was constructed to more comprehensively evaluate the spatiotemporal distribution of the eco-environment quality in the middle reaches of the Yangtze River where urbanization has been developing rapidly. Future trends in eco-environmental quality were analyzed using Theil–Sen trend analysis, the Mann–Kendall test, and the Hurst exponent. Environmental influencing factors were also analyzed. Our results show that: (1) The impact of pollution factors on urban agglomerations cannot be overlooked. The MRSEI model introduces a pollution indicator to better assess the eco-environmental quality of urban agglomeration areas. (2) The eco-environmental quality is high in the south and east and low in the north and west, with overall levels ranging between moderate and good. (3) The eco-environmental quality remained stable, improved, and degraded in 86.3%, 3.1%, and 10.7% of the study area, respectively. (4) The land use and land cover type are directly related to the eco-environment. Climate factors indirectly affect the eco-environment. Human activities in cities and urban peripheries lead to land use changes and industrial pollution, which significantly affect environmental quality. Full article