Search Results (325)

The exploration of the coupling trend between urban agglomeration development (UAD) and land surface temperature (LST) expansion is of great significance, and it is of scientific value for the regulation of the thermal environment of urban agglomerations, the optimization of urban spatial planning, and the achievement of sustainable urban development. This study employs an array of remote sensing datasets from multiple sources—employing a multi-faceted approach encompassing an overall coupling situation analysis model, a coordination and evaluation system, a geographically weighted spatial autocorrelation algorithm, and landscape pattern quantification indicators—to explore the mutual feedback mechanism and spatial coupling characterization of LST and UAD in the Guanzhong Plain Urban Agglomeration (GZPUA). The results of the study can provide data support for urban spatial planning and thermal environment regulation. The results indicate the following findings: (1) In the GZPUA, the nighttime light (NTL) and land surface temperature (LST) centroids show a significant tendency toward approaching one another, with a spatial offset decreasing from 45.0 km to 9.1 km at the end, indicating a strengthening trend in the photothermal system’s coupling synergy. (2) The coordination of light and heat in the study area exhibits significant non-equilibrium development, with a dynamic trend of urban development space shifting towards the southwest. It confirms the typical regional response law of rapid urbanization. (3) The Moran’s I index of the photothermal system in the study area increased from 0.289 to 0.335, an increase of 15.9%. The proportion of “high–high” (H-H)/“low–low” (L-L)-type regions with clustering distribution of cold and hot spots reaches 58.01%, and their spatial continuity characteristics are significantly enhanced, indicating a significant trend of spatial structural integration between urban heat island effect and construction land expansion. Full article

Investigating the coupling coordination between urban scale and vitality is critical for enhancing holistic urban development quality and advancing sustainability. Taking the Changsha-Zhuzhou-Xiangtan (ChangZhuTtan) metropolitan area as a case study, this research integrates multi-source raster and vector data to: (1) analyze spatial patterns of urban scale and virtual–substantive vitality; (2) delineate a “scale-vitality” hierarchical zonal structure; (3) quantify coupling relationships across subzones; and (4) propose synergistic spatial optimization strategies. Key findings reveal that, distinct core-periphery structure characterizes urban scale and vitality, with Changsha’s central districts dominating population, land use, and economic metrics, while Zhuzhou and Xiangtan exhibit moderate concentrations. Significant positive correlations exist between urban scale and dual vitality types, with scale-driven vitality enhancement being most pronounced in core agglomeration zones. Furthermore, in the metropolitan core, where both urban scale and vitality values are high, they exhibit a high-value coupling state. As they expanded outward, both metrics gradually decreased, resulting in a low-value coupling state. However, zonal comparisons (core agglomeration circle–peripheral expansion circle) reveal that the proportion of spatially coupled units progressively increases. By elucidating scale-vitality coupling in the ChangZhuTtan metropolitan area, this study provides actionable insights for spatial planning and sustainable urban transition. The methodology framework is replicable for similar metropolitan regions globally. 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

This study investigates the spatiotemporal changes in land use within the urban agglomeration on the northern slopes of the Tianshan Mountains (TNUA), aiming to identify the driving factors and provide a scientific basis for regional ecological protection, rational land use planning, and sustainable resource utilization. Using land use data, we analyzed transitions, dynamics, intensity, and gravity shifts in land use, examined driving mechanisms using geographic detectors, and simulated future land use patterns with the Patch-generating Land Use Simulation (PLUS) model. The results indicate that between 2010 and 2020, forest, water body, and unused land areas decreased, while cropland, grassland, and construction land expanded. The rate of land use change accelerated significantly, increasing from 0.0955% during 2010–2015 to 0.3192% during 2015–2020. The comprehensive land use dynamic degree index rose from 157.8371 to 161.1008, with Shayibake District exhibiting the most rapid growth. Precipitation, temperature, economic development, and elevation were the dominant driving factors throughout the study period. Population density had the strongest influence on the expansion of water body, while slope was the most significant factor for cropland expansion. Nighttime light was the primary driver of construction land growth. Projections for 2025, 2030, and 2035 suggest a continued decline in unused land and forest areas, alongside increases in cropland, grassland, water body, and construction land. Full article

The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is one of China’s three major urban agglomerations. Over the past thirty years, the region has undergone intensive economic development and urban expansion, resulting in significant changes in its ecological conditions. Due to the region’s humid and rainy climate, traditional remote sensing ecological indexes (RSEIs) struggle to ensure consistency in long-term ecological quality assessments. To address this, this study developed a unified RSEI (URSEI) model, incorporating optimized data selection, composite index construction, normalization using invariant regions, and multi-temporal principal component analysis. Using Landsat imagery from 1990 to 2020, this study examined the spatiotemporal evolution of ecological quality in the GBA. Building on this, spatial autocorrelation analysis was applied to explore the distribution characteristics of the URSEI, followed by geodetector analysis to investigate its driving factors, including temperature, precipitation, elevation, slope, land use, population density, GDP, and nighttime light. The results indicate that (1) the URSEI effectively mitigates the impact of cloudy and rainy conditions on data consistency, producing seamless ecological quality maps that accurately reflect the region’s ecological evolution; (2) ecological quality showed a “decline-then-improvement” trend during the study period, with the URSEI mean dropping from 0.65 in 1990 to 0.60 in 2000, then rising to 0.63 by 2020. Spatially, ecological quality was higher in the northwest and northeast, and poorer in the central urbanized areas; and (3) in terms of driving mechanisms, nighttime light, GDP, and temperature were the most influential, with the combined effect of “nighttime light + land use” being the primary driver of URSEI spatial heterogeneity. Human-activity-related factors showed the most notable variation in influence over time. 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

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

Land use change significantly influences landscape pattern adjustments, thereby altering ecosystem functions and service flows, ultimately impacting ecosystem service value (ESV). However, previous studies have often examined the impacts of land use change and landscape patterns on ecosystem services from a one-dimensional perspective, overlooking the complex interactions among these factors. This study proposes a “process–structure–value” response framework and applies it to a case study of the western Sichuan urban agglomeration. Its aim is to identify the spatial and temporal characteristics of land use and landscape pattern evolution. Additionally, it quantitatively evaluates the synergistic effects of these changes on ESV evolution from 2000 to 2020 using a correlation analysis. The results show that, over the past 20 years, the study area experienced a significant expansion of construction land by 184,729.41 hm², leading to the dispersion and fragmentation of arable land, grassland, and waters, resulting in an overall trend of fragmentation and diversification in landscape patterns. The ESV increased by CNY 2.619 billion, primarily due to the increased ESV associated with forest land and waters. This study found that the synergistic effects of land use processes and landscape pattern structures significantly enhanced ESV. The transition from construction land and arable land to forest land and waters notably improved the ESV. Meanwhile, increased landscape diversity and patch connectivity further enhanced the ecosystem service function. Furthermore, the ecological environment of the study area remained vulnerable despite the increased ESV. Overall, the results highlight the significant correlation between changes in land use processes, landscape patterns, and ESV, emphasizing the necessity of integrating the “process–structure–value” framework in future research to comprehensively assess the responses of land use and landscape patterns to ESV, providing a more comprehensive reference for land use planning and policy development. Full article

With accelerating urbanization, urban expansion poses a significant threat to biodiversity, especially to endemic species, which are more sensitive to land use changes. However, to date, the impacts of future urban expansion at the species level in China on endemic species remain unclear. This study aims to comprehensively evaluate the impact of future urban expansion on endemic species in China under the framework of the shared socioeconomic pathways (SSPs) from 2015 to 2050 using multiple indicators, including suitable habitat area changes, habitat fragmentation, and species extinction risk. The results show that from the perspective of suitable habitat loss and extinction risk, the negative impact of urban expansion in China from 2015 to 2050 may be greater for endemic species than for other species with a wide distribution. In addition, more than 56% of the affected species suffer from exacerbated habitat fragmentation. Biodiversity loss is more serious in regions with high endemic species richness and in urban agglomerations with rapid urban development in the future. Endemic birds and amphibians show high sensitivity to threats of urban expansion from various perspectives. This study provides a basis for biodiversity conservation, guiding the balance between urban development and biodiversity protection. Full article

Rural homestays have emerged as pivotal drivers of rural socioeconomic revitalization, particularly in metropolitan peripheries characterized by intensified urban–rural dynamics. However, their spatiotemporal distribution patterns and underlying mechanisms remain underexplored. This study employs Geodetector and related analytical methods to examine rural homestays in Beijing, aiming to decipher spatial heterogeneity and driving factors. The results reveal a distinct “large-scale dispersion with small-scale clustering” pattern marked by pronounced agglomeration in northern mountainous areas and sparse distributions in southern suburban regions. Temporally, the sector currently exhibits a notable expansion–contraction phase influenced by external factors, alongside spatial centroid migration toward resource-rich zones. Geodetector quantification identifies the proximity to transportation nodes and vegetation coverage as primary spatial determinants, while socioeconomic factors demonstrate comparatively limited influence—contrasting sharply with urban contexts. Rural homestay concentration zones are classified into high-, medium-, and low-intensity categories based on the homestay density, with high-intensity zones leveraging apex advantages of scenic resources, cultural heritage, and infrastructure. These findings underscore the interplay of natural environmental factors, tourism resources, transportation accessibility, and socioeconomic conditions in shaping agglomeration dynamics, providing actionable insights for optimizing spatial planning and promoting sustainable development in rural regions adjacent to megacities. Full article

Public service facilities are the cornerstone of urban development and further expansion, and their spatial distribution fairness is closely related to the quality of life of urban residents. Existing research tends to focus on coverage analysis of a single city or a single type of public service facility, lacking a macro perspective at a medium-to-large scale and consideration of residents’ public service needs. To improve the monitoring of urban public service facility coverage and supply–demand patterns, this paper adopts an urban diagnostic perspective, using 14 megacities from nine urban agglomerations in China as the study area. By integrating spatial and temporal social sensing big data, including road networks, population, and points of interest (POI) data, and employing spatial analysis methods including coverage rate calculation, supply–demand matching efficiency, spatial heterogeneity, and sp{atial stability analysis, this study reveals the spatial distribution patterns of various facilities within cities, as well as the heterogeneity, balance, and equity of supply–demand matching efficiency between different cities. The results show that the spatial distribution of public service facilities in different cities generally tends to concentrate in the central areas, although there are some variations due to local topographical influences. The coverage rate of transportation and education facilities is relatively high, while that of healthcare facilities is generally lower. This study provides information support for urban planning and the optimization of public service facility allocation, contributing to the achievement of sustainable urban development through the comprehensive analysis and comparison of 14 megacities. Full article

Promoting the development of low-carbon renewable energy is crucial for meeting the growing energy demand, reducing dependence on fossil fuels, and controlling carbon dioxide emissions. Clarifying the spatiotemporal characteristics of regional renewable energy production and its influencing factors will help optimize the spatial layout of renewable energy production and provide a solid theoretical basis for coordinating the development of all aspects of renewable energy production. Using panel data from 22 districts and counties in Ningxia from 2014 to 2021, this study employed the spatial Gini coefficient, Moran’s I index, standard deviational ellipse, and geographical detector to analyze the spatiotemporal evolution patterns and influencing factors of renewable energy production development in Ningxia. The results indicate that renewable energy production in Ningxia exhibits significant spatial agglomeration and autocorrelation. Temporally, renewable energy production shows a spatial expansion trend characterized by dynamic agglomeration patterns. The coupling degree between renewable energy generation and the spatial distribution of power production is relatively high, with notable regional disparities. Urbanization level, urban population, per capita GDP, and industrial SO₂ emissions have a positive impact on renewable energy production, while energy intensity and environmental regulation show insignificant effects. To further promote the development of renewable energy, Ningxia should strengthen power infrastructure construction at the county level, enhance the radiating and driving effects of high-value areas on surrounding cities and counties, optimize the spatial layout of power facilities based on the agglomeration trajectories of renewable energy production, integrate multiple types of renewable energy to improve overall generation efficiency and system stability, and encourage local enterprises to increase technological and economic investments in renewable energy, thereby advancing sustainable energy transition and achieving high-quality development in resource-based regions. Full article

In the context of high-quality economic development, the empowering effect of regional integration policies on urban green and low-carbon development has significantly strengthened, playing a crucial strategic role in achieving the coordinated development of the economy and ecology. This study uses the expansion of the Yangtze River Delta urban agglomeration as a quasi-natural experimental scenario, analyzing the pathways and mechanisms through which regional integration policies influence urban green and low-carbon development based on panel data from Chinese cities between 2004 and 2022, using a multi-period Difference-in-Differences (DID) model. The empirical results show the following: ① Regional integration policies significantly enhance the efficiency of urban green and low-carbon development, a conclusion that remains robust after a series of robustness tests, including PSM-DID estimation, placebo tests, instrumental variable methods, indicator reconstruction, and policy interference exclusion. ② Mechanism tests reveal that regional integration policies mainly drive the green and low-carbon transformation through three channels: innovation investment, industrial upgrading, and talent aggregation. ③ Heterogeneity analysis indicates that the positive impact of regional integration policies on the green and low-carbon development of cities is more significant in eastern regions, resource-based cities, small and medium-sized cities, and old industrial cities. Spatial effect tests show that regional integration development has a significant spatial spillover effect on urban green and low-carbon transformation. Based on these findings, it is recommended that, in the future, in global efforts should be made to continuously improve the regional collaborative governance system, strengthen multi-dimensional linkage mechanisms in urban agglomerations, and build a policy support framework that drives innovation and optimizes the allocation of factors. This study not only provides empirical support for the green efficiency enhancement mechanisms of regional integration policies but also offers decision-making references for promoting regional coordinated development and achieving green economic growth in the digital economy era. Full article

Rural tourism has become a key driver of rural revitalization in China, contributing to poverty alleviation while also irreversibly altering the spatial evolution of rural settlements. In the ecologically fragile regions of northwest China, the rapid expansion of rural tourism destinations has raised ecological concerns, particularly regarding land resource utilization. Therefore, it is crucial to examine the phenomenon of industrial agglomeration in the evolution of rural tourism within the context of tourism-driven poverty alleviation. This study uses Lanzhou City as a case study and employs nearest neighbor analysis and kernel density estimation to analyze the spatial agglomeration patterns of rural tourism destinations, focusing on agglomeration forms, scales, and patterns. Additionally, it explores the spatial coupling distribution between agglomeration levels and influencing factors. The results show that from 1987 to 2022, the development of rural tourism destinations in Lanzhou City has progressed through several stages, from initial emergence to rapid growth. The form of industrial agglomeration has shifted from a dispersed to a clustered distribution, gradually expanding from urban centers to peripheral areas. The spatial agglomeration follows a multi-core hierarchical point-axial diffusion model, forming multiple core and sub-core agglomeration zones of varying scales. This transformation is primarily driven by geographical factors, transportation accessibility, and the presence of high-quality tourist attractions. However, a comparison of land use changes and ecological vulnerability indices over multiple periods indicates that the industrial agglomeration of rural tourism has led to irregular land use patterns and ecosystem instability. Finally, based on the complex relationship between rural tourism development, industrial agglomeration, and ecological sustainability, this study proposes strategies for the development of rural tourism in Lanzhou City, with the aim of providing valuable insights for the development of rural tourism in ecologically fragile regions of China. Full article