Search Results (136)

Historical towns embody the origins and continuity of urban civilization, preserving distinctive spatial fabrics, cultural lineages, and latent economic value within contemporary metropolitan systems. Their integrated conservation directly aligns with SDG 11.4, and advances the holistic preservation objectives of historic urban landscapes (HULs). However, achieving these objectives cannot be solely dependent on modern remote sensing technologies; it necessitates the integration of historical geographic information system (HGIS) theoretical frameworks and methodological approaches. Leveraging HGIS and multisource data—including SDGSAT-1 nighttime light imagery, textual documents, and historical maps—this study reconstructed the spatial extent of historical towns in suburban Shanghai and assessed their present-day economic vitality through light-based spatial proxies. Key results comprised the following. (1) Most suburban historical towns are small, yet nighttime light intensity varies markedly. Jiading County, Songjiang Prefecture, and Jinshan Wei rank highest in both spatial extent and brightness. (2) Town area exhibits a strong positive relationship (R² > 0.80) with the total nighttime light index, indicating that larger settlements generally sustain higher economic activity. (3) Clusters of “low area–low light” towns showed pronounced intra-regional disparities in economic vitality, underscoring the need for targeted revitalization. (4) Natural setting, historical legacy, policy interventions, and transport accessibility jointly shape development trajectories, with policy emerging as the dominant driver. This work demonstrates a transferable framework for multidimensional assessment of historical towns, supports differentiated conservation strategies, and aids the synergistic integration of heritage preservation with regional sustainable development. Full article

This study investigates how various renewable energy technologies influence national carbon intensity (CO₂ emissions per unit of GDP) across 184 countries over the period 2000–2020. In the context of Sustainable Development Goals (SDG 7 and SDG 13) and the post-Paris-Agreement policy landscape, it addresses the gap in understanding technology-specific decarbonization effects and the role of governance. A dynamic panel framework employing the Dynamic Common Correlated Effects (DCCE) estimator accounts for cross-sectional dependence and temporal persistence, while disaggregating total renewables into hydropower, wind, solar, and geothermal generation. Environmental regulation is incorporated as a moderating variable using the World Bank’s Regulatory Quality index. Empirical results demonstrate that higher renewable generation is associated with statistically significant reductions in carbon intensity, with hydropower showing the most consistent negative effect across all income groups. Solar and geothermal technologies yield substantial carbon-reducing impacts in lower-middle-income settings once supportive policies are in place. Wind exhibits heterogeneous outcomes: positive or insignificant effects in some high- and upper-middle-income panels prior to 2015, shifting toward neutral or negative after more stringent regulation. Interaction terms reveal that stronger regulatory environments amplify renewable-driven decarbonization, particularly for intermittent sources such as wind and solar. Key contributions include (1) a comprehensive global assessment of four disaggregated renewable technologies; (2) integration of regulatory quality into decarbonization pathways, illustrating post-2015 policy moderations; and (3) methodological advancement through a large-sample DCCE approach that captures unobserved common shocks and heterogeneous country dynamics. These findings inform targeted policy measures—such as prioritizing hydropower where feasible, strengthening regulatory frameworks, and tailoring technology strategies—to accelerate low-carbon energy transitions worldwide. Full article

As a crucial component of the Beijing–Hangzhou Grand Canal’s hydraulic engineering, the Jiangnan Canal has historically played a pivotal role in China’s development as a key hydraulic infrastructure. This water conservancy project, connecting northern and southern water systems, not only facilitated regional economic integration but also nurtured unique cultural landscapes along its course. The Jiangnan Canal and its adjacent cities were selected as the study area to systematically investigate 334 tangible cultural heritage (TCH) sites and 420 intangible cultural heritage (ICH) elements. Through integrated Geographical Information System (GIS) spatial analyses—encompassing nearest neighbor index, kernel density estimation, standard deviation ellipse assessment, multi-ring buffer zoning, and Geodetector modeling, the spatiotemporal distribution features of cultural heritage were quantitatively characterized, with a focus on identifying the underlying driving factors shaping its spatial configuration. The analysis yields four main findings: (1) both TCH and ICH exhibit significant spatial clustering patterns across historical periods, with TCH distribution displaying an axis-core structure centered on the canal, whereas ICH evolved from dispersed to clustered configurations. (2) The center of gravity of TCH is primarily around Taihu Lake, while that of ICH is mainly on the south side of Taihu Lake, and the direction of distribution of both is consistent with the direction of the canal. (3) Multi-ring buffer analysis indicates that 77.2% of TCH and 49.8% of ICH clusters are concentrated within 0–10 km of the canal, demonstrating distinct spatial patterns: TCH exhibits a gradual canal-dependent density decrease with distance, whereas ICH reveals multifactorial spatial dynamics. (4) Human activity factors, particularly nighttime light intensity, are identified as predominant drivers of heritage distribution patterns, with natural environmental factors exerting comparatively weaker influence. These findings provide empirical support for developing differentiated conservation strategies for canal-related cultural heritage. The methodology offers replicable frameworks for analyzing heritage corridors in complex historical landscapes, contributing to both applied conservation practices and theoretical advancements in cultural geography. Full article

Exploring the spatiotemporal evolution characteristics of land use/cover change (LUCC) and landscape ecological risk (LER), and understanding their coupling mechanisms are crucial for sustainable development in ecologically vulnerable areas. This study examines the Wanzhou–Dazhou–Kaizhou (WDK) region from 1980 to 2020, employing intensity analysis, comprehensive index of land use intensity (LUI), and landscape index models to analyze the spatiotemporal evolution patterns of LUCC and LER systematically. A coupling research framework based on optimal evaluation scales was constructed to reveal the interactive mechanisms between LUI and LER. The results indicate that over the 40 years, the main land use categories were Crop and Forest. Crop was the primary stable source for the expansion of Built. LUI and LER exhibited a clear geographic gradient, higher in the south and lower in the north, with agricultural and urban areas showing higher risk levels. The coupling coordination degree between LUI and LER was generally moderate, spatially manifesting as a “strong coupling–weak coordination” pattern. Moderately unbalanced areas increased, with environmental improvements observed in some regions. However, typical ecological degradation zones also emerged. This study can provide a basis for environmental management and land use planning in the WDK region. Full article

As China’s third national-level new area, Xiong’an New Area plays a pivotal strategic role in relocating non-capital functions from Beijing while serving as a model for sustainable urban development. This study investigates the spatiotemporal evolution of ecosystem service value (ESV) and landscape patterns in Xiong’an before (2014–2016) and after (2017–2022) its establishment, assessing the policy-driven impacts of green development initiatives. Using remote sensing data, random forest classification, and landscape pattern analysis, we quantified land use dynamics, landscape index, and ESV variations. Key findings reveal significant land use transformations, with cultivated land declining by 7.51% and coniferous forest expanding by 189.84%, driven by urbanization and afforestation efforts. The comprehensive land use dynamic degree reached 4.96% (2014–2022), while the land use intensity index decreased by 20.95%. Concurrently, the fragmentation index increased significantly (Diversity Index (SHDI) +45%; Edge Density (ED) +66.23%). Despite these changes, ESV surged by 57.51% (CNY 334.63 billion), primarily due to wetland and forest expansion. Statistical analysis revealed positive correlations between ESV and the fragmentation index (ED, NP, and SHDI), whereas the aggregated index (CONTAG and AI) exhibited negative correlations. The findings substantiate the policy effectiveness of Xiong’an’s ecological initiatives, revealing how strategic landscape planning can balance urban development with ecosystem protection, offering valuable guidance for sustainable urbanization in Xiong’an and comparable regions. Full article

Urban ecological resilience (UER) is vital for sustainable development, enabling cities to maintain stability in the face of environmental challenges. This study combined landscape pattern indices and spatial measurement methods, establishing a multi-scale linked “Resistance-Adaptation-Recovery (Res-Ad-Rec)” model chain to assess the UER of Xuzhou City, analyzed spatiotemporal changes using Moran’s I indices, and explored the influencing factors through the Multi-scale Geographically Weighted Regression (MGWR) model. Finally, the research framework of “three-dimensional assessment, spatial diagnosis, and mechanism analysis” was constructed to achieve a multi-dimensional dynamic analysis. The results showed the following: (1) UER declined from 2008 to 2022, with low-value areas expanding from the city center and high-value areas near water bodies. (2) The spatial autocorrelation of UER was significant, with a rise in Global Moran’s I index and the strongest spatial agglomeration effect observed in 2022. High–high and low–low clustering were the main characteristics of local spatial autocorrelation. (3) Population density and nighttime lighting intensity were major factors influencing the spatial distribution of UER in Xuzhou City. The findings can provide a useful reference for similar resource transition cities to explore the path of sustainable development. Full article

Industrial parks are key contributors to localized urban heat intensification, forming sub-industrial heat islands (IHIs) that influence the urban thermal environment. This study investigates the industrial heat island effect (IHIE) in the Guangzhou–Foshan metropolitan area (GFMA), with a generalized additive model (GAM) to explore the influence of park spatial patterns and land cover characteristics, using indicators such as industrial heat island intensity (IHII), industry warming area (IWA), industry warming efficiency (IWE), and industry warming gradient (IWG). The results show that (1) industrial land significantly contributes to industrial heat islands (IHIs), with heat extending up to 200 m into surrounding areas. (2) IHIE intensity varies notably across park types, with each dominated by different factors: manufacturing parks by landscape shape index (LSI); comprehensive parks by impervious surfaces (IWS) and internal building land (IB); and special parks primarily by IB. (3) In most industrial parks, park area (S), IWS, and LSI are the key factors affecting IHIE. As IWS increases, IHIE strengthens, though this trend can be mitigated by expanding park area. Conversely, a higher LSI weakens IHIE. (4) Several variables, including arable land (AL) and water body (WB), exhibited nonlinear or threshold effects, suggesting that IHIE is shaped by complex mechanisms. These findings offer valuable insights for optimizing land use in urban and industrial planning to reduce IHIE and promote sustainable urban development. Full article

Urban agglomeration ecosystems are impacted by human activities and natural disasters, so analyzing the spatial and temporal evolution of landscape ecological resilience from the perspective of adaptive cycling is crucial. Using the Changsha–Zhuzhou–Xiangtan urban agglomeration in China as a case study, this research constructs a “Risk-Potential-Connectivity” framework to evaluate ecological resilience. This framework applies exploratory spatial data analysis methods to examine the spatiotemporal evolution and associated patterns of resilience and the Geodetector model to measure the driving factors of spatial variation. This study constructs an adaptive cycle model based on ecological resilience analysis, integrating potential and connectivity indices to classify the development stages of urban agglomeration regions dynamically. The results showed that the overall spatial distribution pattern of ecological risk decreased from the center outward, whereas ecological potential and connectivity increased. The average resilience index from 2000 to 2020 was 0.31, with a declining trend and shifting center of gravity from northwest to southeast. The spatial and temporal distribution of toughness exhibited high and low aggregation, with an overall Moran index greater than 0.75. Land-use intensity had the strongest explanatory power (q = 0.3662) for the spatial differentiation of landscape ecological resilience drivers and the joint effects of factor interaction had a higher explanatory power than single factors. Adaptive cycle analysis revealed that Furong District is in the protection stage, Xiangtan County in the development stage, and Liling City in the reorganization stage, with no region yet in the release stage. The findings offer a better understanding of the interactive adaptation characteristics and evolutionary patterns of social-ecological systems over extended periods, providing scientific support for the formulation of protection strategies to respond to dynamic changes in urban agglomeration ecosystems. Full article

Investigating spatio-temporal differentiation patterns of land-use conflicts in mountainous and flatland regions provides critical insights for optimizing spatial regulation strategies and advancing sustainable regional development. Using the Urban Agglomeration in Central Yunnan (UACY) as a case study, the production–living–ecological space (PLES) was classified through land-use functional dominance analysis based on 2010–2020 geospatial datasets. Spatio-temporal evolution patterns and mountain–dam differentiation were analyzed using spatial superposition, dynamic degree analysis, transfer matrices, and geospatial TuPu methods. A multi-scale conflict index incorporating landscape metrics was developed to assess PLES conflict intensities across spatial scales, with contribution indices identifying key conflict-prone spatial types. Analysis revealed distinct regional differentiation in PLES distribution and evolutionary trajectories during 2010–2020. Forest Ecological Space (FES) and Agricultural Production Space (APS) dominated both the entire study area and mountainous zones, with APS exhibiting particular dominance in dam regions. Grassland Ecological Space (GES) and Other Ecological Space (OES) experienced rapid conversion rates, contrasting with stable or gradual expansion trends in other space types. Change intensity was significantly greater in mountainous zones compared to flatland area (FA). PLES conflict exhibited marked spatial heterogeneity. FA demonstrated substantially higher conflict levels than mountainous zones, with evident scale-dependent variations. Maximum conflict intensity occurred at the 4000 m scale, with all spatial scales demonstrating consistent escalation trends during the study period. ULS, FES, and WES predominantly occurred in low-conflict zones characterized by stability, whereas APS, Industrial and Mining Production Space (IMPS), RLS, GES, and OES were primarily associated with high-conflict areas, constituting principal conflict sources. Full article

Intensive mining activities in the Zhungeer open-pit coal mining area of China have resulted in drastic changes to land use and landscape patterns, severely affecting the ecological quality and stability of the region. This study integrates 36 years (1985–2020) of Landsat multiband remote sensing imagery with 30 m resolution CLCD land cover data, establishing a “Sky–Earth–Space” integrated monitoring system. This system allows for the calculation of ecological indices and the creation of land use transition matrices for internal and external regions of the mining area, ultimately completing an assessment of the ecological stability of the Zhungeer open-pit coal mining region. By overcoming the limitations posed by a singular data source, it facilitates a dynamic analysis of the interrelationships among mining activities, vegetation responses, and engineering remediation efforts. The findings reveal a significant transformation among various land types within the mining area, with both the area of mining pits and the area rehabilitated through artificial restoration undergoing rapid increases. By 2020, the area of the mining pits had reached 2630.98 hectares, while the area designated for rehabilitation had expanded to 2204.87 hectares. Prior to 2000, bare land and impermeable surfaces dominated the internal area of the mine; however, post-2000, the Normalized Difference Built-up Index (NDBI) value continuously decreased to −0.0685, indicative of an ecological transition where vegetation became predominant. The beneficial impacts of rehabilitation efforts have effectively mitigated the adverse environmental consequences of open-pit coal mining. Since 2000, the mean Normalized Difference Vegetation Index (NDVI) within the mining area has shown a consistent increase, recovering to 0.2246, signifying a restoration of the internal ecological environment. Moreover, this area exerts a notable radiative influence on the vegetation conditions outside the mining zone, with a contribution value of 1.016. Following rehabilitation efforts, the landscape patch density, landscape separation, and landscape fragmentation in the Zhungeer open-pit coal mining area exhibited a declining trend, leading to a more uniform distribution of landscape patches and improved structural balance. By 2020, the adaptability index had risen to 0.35836, achieving 93.69% of the restoration level observed prior to mining operations in 1985, thus indicating an improvement in ecosystem stability and the restoration of ecological functions, although rehabilitation efforts display a temporal lag of 10 to 15 years. The adverse impacts of open-pit coal mining on the regional ecological environment are, in fact, predominantly short-term. However, human intervention has the potential to reshape the ecology of the mining area, enhance the quality of the ecological environment, and foster the sustained development of regional ecological health. Full article

Understanding the interdependencies among production, living, and ecological spaces (PLESs) is critical for sustainable regional development. Urban fringe areas, shaped by rapid urbanization and conflicting land-use demands, are particularly vulnerable to spatial tensions. This study analyzes the spatiotemporal dynamics and drivers of PLES conflicts in Zengcheng District, Guangzhou, a representative urban fringe region. Using land-use data from 2010 to 2020, the study applies the optimal parameter geographic detector, chosen for its ability to untangle complex spatial interactions, to quantify conflict intensity and identify key drivers. This method was chosen over other spatial analysis techniques due to its ability to effectively capture nonlinear relationships and interaction effects between variables, which traditional regression-based or spatial autocorrelation methods often fail to fully address. The results indicate that production and ecological lands dominated the landscape, while living space expansion slowed, leading to escalating conflicts, particularly in the southern and central regions. The PLES conflict index shows that severe conflict units rose from 0.89% in 2010 to 2.15% in 2020, despite over 80% of spatial units remaining stable. Moderate conflicts peaked in 2015 before declining, while stronger conflicts intensified, especially in rapidly urbanizing areas. Conflict hotspots were most pronounced in rapidly urbanizing zones, particularly at the interface of urban expansion and ecological conservation areas. Moreover, the driving forces behind these conflicts transitioned from economic and urbanization factors to a multifaceted interplay of natural and social determinants, underscoring the growing intricacy of spatial dynamics. These findings offer crucial insights into the mechanisms driving PLES conflicts, guiding urban planners and policymakers in developing strategies to balance competing land-use priorities. By quantifying conflicts and identifying key drivers, this study helps prioritize interventions that mitigate tensions between production, living, and ecological spaces, supporting policies that reconcile urban expansion with ecological preservation for sustainable development in urban fringe areas. Full article

The urban heat island effect, triggered by global warming and rapid urbanization, has negatively impacted residents’ lives. It has been shown that urban green space (UGS) can improve the urban thermal environment. However, the stability and influencing factors of the urban green space cooling effect (UGSCE) in the context of climate change remain unclear. In this paper, we study the area within the Fifth Ring Road of Changchun City, using multi-source remote sensing image data to quantify and analyze the influencing factors of the cooling effect of urban green space and its stability on both regional and patch scales. The results show that on the regional scale, urban green spaces in Changchun have a strong cooling effect on the surrounding environment, which increases with the surface temperature (LST). However, there is a large fluctuation in the cooling effect. On the patch scale, the cooling effect of 35 green spaces showed a small increasing trend from 2013 to 2024. The cooling extent (CE) was more stable across temperatures relative to the cooling intensity (CI). Factors such as the green space area (A), perimeter (P), landscape shape index (LSI), and mean enhanced vegetation index (MEVI) had different degrees of influence on the cooling effect of green space and its stability. Green spaces with a high MEVI had a stronger cooling effect and stability. Based on this, planning suggestions such as increasing vegetation amount, maintaining green space area, optimizing green space morphology, and focusing on blue–green space are proposed to enhance the cooling effect of urban green space and its stability, which would improve the thermal environment of the city and enhance the comfort of residents. This study provides a reference basis for the scientific planning of urban green space and provides a scientific basis and practical guidance for the sustainable development of the city. Full article

Historically, the Wei River has served as part of the Yongji Canal section of the Grand Canal, playing a crucial role in connecting northern and southern China. However, with the acceleration of urbanization in China, issues such as excessive land development and ecological landscape fragmentation have emerged. Exploring the mechanisms of landscape fragmentation evolution in the Wei River basin and proposing optimization strategies is of significant importance for land use and ecological stability within small- to medium-sized river basins. This study selected land use data from the Weihe River basin between 2000 and 2020, using landscape pattern indices to analyze the trend of landscape fragmentation. The principal component analysis (PCA) and geographical detector methods were employed to explore the distribution characteristics and driving factors of landscape fragmentation. The research results indicate that: (1) The degree of landscape fragmentation in the Wei River basin has progressively intensified over time. The edge density index (ED), the landscape division index (DIVISION), the landscape shape index (LSI), and the Shannon diversity index (SHDI) have increased annually, while the contagion index (CONTAG) and area-weighted mean patch size (Area_AM) have continuously decreased; (2) Landscape fragmentation in the Wei River basin is characterized by stable changes in the source and tributary fragmentation areas, a concentrated distribution of fragmentation in the tributaries, and a significant increase in fragmentation in the main stream; (3) The analysis using the geographic detector method indicates that vegetation coverage (FVC), human activity intensity (HAI), and land use/land cover change (LUCC) are the main driving factors of landscape fragmentation in the Wei River basin. The findings explore the mechanisms of landscape fragmentation in the basin and provide a reference for land use planning and ecological restoration in the region. Full article

Rapid urbanization is causing ecological and environmental issues to worsen. The stability of the ecosystem function of the farming–pastoral ecotone (FPE) in Inner Mongolia is essential to ensuring the sustained growth of the nearby cities, acting as a vital ecological safeguard in China’s northern regions. This study used the “production–living–ecological” spaces (PLES) spatial dynamics, the rate of change index, and the standard deviation ellipse to examine the spatial and temporal evolution of the PLES in the FPE in Inner Mongolia. This study constructed a spatial conflict index model based on the theory of landscape ecology, and evaluated the ecosystem service value (ESV) of the region and visualized the results of the analysis using the micro-scale of the grid. Finally, the relationship between the ESV and PLES spatial conflicts was determined using a bivariate spatial autocorrelation model. The findings show that: (1) During the 20 years, the maximum ecological spatial change rate reached 0.43%, with the cumulative spatial dynamics of PLES totaling 2.49%. Notably, industrial production space activities experienced the most significant increase, amounting to 277.09%. (2) Regional spatial conflict intensity shows an upward trend from 2000 to 2020, with the average conflict level increasing from 0.53 to 0.56, and high conflict values being concentrated in the east. (3) The ESV pattern in the FPE in Inner Mongolia is characterized by “high ESV in the east and low ESV in the central and western regions”, with an overall trend of increasing and then decreasing. A notable negative correlation was observed between ESV and PLES spatial conflicts in the region, with Moran’s I indicating values of−0.196, −0.293, and−0.163, respectively. Specifically, low-value–high-conflict zones were predominantly found in other ecological spaces, high-value–low-conflict zones was concentrated in forest ecological spaces, and high-value–high-conflict zones were predominantly concentrated in aquatic ecological spaces. The research findings serve as a crucial scientific foundation for the development of ecological civilization and the sustainable advancement of the FPE in Inner Mongolia. Full article

The uncontrolled expansion of mining activities has caused severe environmental impacts in semi-arid regions, endangering fragile ecosystems and water resources. This study aimed to propose a decision-making model to identify land use and land cover changes in the semi-arid region of Pernambuco, Brazil, caused by mining through a spatiotemporal analysis using high-resolution images from the PlanetScope satellite constellation. The methodology consisted of monitoring and evaluating environmental impacts using the k-Nearest Neighbors (kNN) algorithm, spectral indices (Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI)), and hydrological data, covering the period from 2018 to 2023. As a result, a 3.28% reduction in vegetated areas and a 6.62% increase in urban areas were identified over five years, suggesting landscape transformation, possibly influenced by the expansion of mining and development activities. The application of kNN yielded an Overall Accuracy (OA) greater than 99% and a Kappa index of 0.98, demonstrating the effectiveness of the adopted methodology. However, challenges were encountered in distinguishing between constructions and bare soil, with the Jeffries–Matusita distance (JMD) analysis indicating a value below 0.34, while the similarity between water and vegetation highlights the need for more comprehensive training data. The results indicated that between 2018 and 2023, there was a marked degradation of vegetation and a significant increase in built-up areas, especially near water bodies. This trend reflects the intense human intervention in the region and reinforces the need for public policies aimed at mitigating these impacts, as well as promoting environmental recovery in the affected areas. This approach proves the potential of remote sensing and machine learning techniques to effectively monitor environmental changes, reinforcing strategies for sustainable management in mining areas. Full article