Search Results (22)

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

The urban heat island effect (UHI) has become a major challenge for sustainable urban development. In recent decades, the significant development of urban agglomerations has intensified the complex interaction and comprehensive impact of the UHI effect, but the spatiotemporal pattern of regional heat islands has been poorly understood. Based on the land surface temperature (LST) from 2001 to 2020, this study uses the relative land surface temperature (RLST) method to quantify the regional heat island (RHI) of the Central Yunnan Urban Agglomeration (CYUA) beyond a single city, combines a variety of spatial analysis tools to identify the multi-scale spatiotemporal pattern, and explores the multidimensional driving factors of RHIs. The combined effects of indicators such as urbanization intensity, blue–green space intensity (2D), and building height characteristics (3D) on the mitigation or exacerbation of RHIs are included. The results are as follows: (1) The RHI was significantly enhanced, especially during 2011–2014, when the heat island intensity and influence range expanded rapidly, especially in the core areas such as Kunming and Qujing. (2) The main urban areas of prefecture-level cities have a greater contribution to the RHI, and the intercity heat interaction further intensifies the heat island effect on county-level regions. (3) Different land cover types have different effects on RHI. The human and social factors have a positive effect on the RHI, the blue–green intensity has a strong inhibitory effect, and the cooling effect of blue space is better than that of green space. Topographic and meteorological factors have little influence. To effectively address the challenge of UHI, the CYUA must strengthen the construction of green infrastructure, optimize urban planning, promote energy conservation and emission reduction, and improve climate adaptation planning. This paper discusses the spatiotemporal variation in the heat island effect and the influencing factors from a new regional perspective, which enriches the research content of urban agglomeration thermal environment and improves the research system of the heat island effect. Full article

The evaluation of the carrying capacity of urban resources and the environment and the suitability of urban spatial development (referred to as “double evaluation”) is a fundamental prerequisite for territorial spatial planning. A scientifically planned urban spatial layout is key to balancing economic, social, and environmental benefits, which directly impacts urbanization levels and regional high-quality development. In this study, a double evaluation index system was established for the city cluster in central Yunnan based on the theories of “double evaluation” and main functional zones. The PLUS model was used to predict the distribution of future urban spatial patterns, considering factors like main function zones, and to optimize the spatial patterns of cities and towns in the study area. The findings are as follows. (1) The area of land suitable for urban construction in the study area is 25,107.51 km², mainly distributed in the southern and central urban areas, as well as in the Zhanyi and Qilin districts to the east. (2) More than 76% of the land designated for urban construction is located in suitable areas, with an area of 680.51 km², which represents only 2.71% of the total suitable land, indicating significant potential for further urban development. The PLUS simulation reveals that the urban area in the study area will reach 235.41 km² by the future, with 83.67% of urban construction space concentrated in suitable areas. Additionally, 69.11% of urban construction space and 74.53% of suitable land for urban construction are located in the key development area, which covers 618.43 km² and 18,713.28 km², respectively. This highlights the key development area’s crucial role in urban expansion and its significant potential for further development. Despite the region’s high level of economic activity and urbanization, there remains considerable potential for the expansion of towns over a wide area. This study provides valuable insights for optimizing urban spatial layouts, the allocation of national land space functions, and promoting orderly development. Full article

Land use conflict is an inevitable and objective phenomenon during regional development, with significant impacts on both regional economic growth and ecological security. Scientifically assessing the spatiotemporal evolution of these conflicts is essential to optimize land use structures and promote sustainable resource utilization. This study employs multi-period land use/land cover remote sensing data from China to develop a model for the measurement of land use conflict from the perspective of the landscape ecological risk. By applying the optimal landscape scale method to determine the most appropriate analysis scale, this research investigates the spatiotemporal evolution characteristics of land use conflicts in the Central Yunnan Urban Agglomeration from 2000 to 2020. Furthermore, by integrating the Patch-Generating Land Use Simulation (PLUS) model with the Multi-Objective Programming (MOP) algorithm, this study simulates the spatial patterns of land use conflict in 2030 under four scenarios: Natural Development (ID), Economic Development (ED), Ecological Conservation (PD), and Sustainable Development (SD). The findings reveal that, from 2000 to 2020, the proportion of areas with strong and moderately strong conflict levels in the Central Yunnan Urban Agglomeration increased by 2.19%, while the proportion of areas with weak and moderately weak conflict levels decreased by 1.45%, underscoring the growing severity of land use conflict. The predictions for 2030 suggest that the spatial pattern of conflict under various scenarios will largely reflect the trends observed in 2020. Under the ID scenario, areas with weak and moderately weak conflict levels constitute 57.5% of the region; this increases by 0.85% under the SD scenario. Conversely, areas experiencing strong and moderately strong conflict levels, which stand at 33.02% under the ID scenario, decrease by 1.04% under the SD scenario. These projections indicate that the SD scenario, which aims to balance ecological conservation with economic development, effectively mitigates land use conflict, making it the most viable strategy for future regional development. Full article

Accurately identifying the expansion characteristics and driving mechanisms at different development stages of urban agglomerations is crucial for their coordinated development. Using the Central Yunnan Urban Agglomeration as a case study, we employ a data fusion approach to fuse nighttime light data with LandScan data and utilize the U-net neural network to systematically analyze the expansion characteristics and driving mechanisms of the urban agglomeration. The results indicate that, from 2008 to 2013, the Central Yunnan Urban Agglomeration was in an initial expansion stage, primarily driven by economic development levels and population size. From 2013 to 2018, the agglomeration entered an accelerated expansion stage, driven mainly by industrial structure transformation and the population agglomeration effect. From 2018 to 2023, the agglomeration experienced a steady expansion stage, with industrial structure upgrading and government support as the primary driving forces. Furthermore, we found that, over time, the influence of economic development levels and population size as driving forces gradually weakened, while the impact of industrial structure and government support significantly increased. Through the fusion of multi-source data and analysis of driving mechanisms at different developmental stages, we comprehensively revealed the development trajectory of the Central Yunnan Urban Agglomeration and provided valuable insights for future urban agglomeration development planning and policymaking. Full article

In the current context of urbanization, urban agglomerations face complex challenges in maintaining an ecological balance. This study uses remote sensing images of the Central Yunnan urban agglomeration from 2000 to 2020, along with socioeconomic data, to analyze the spatiotemporal characteristics of the green space evolution. Utilizing dynamic geographically weighted regression analysis based on principal components (PCA-GWR), we identify the key socioeconomic factors influencing these changes and quantitatively analyze the driving forces in each stage. Our findings reveal a continuing trend of decreasing total green space alongside increasing individual forest types and pronounced regional disparities in green space dynamics. The results indicate that socioeconomic factors exert both positive facilitative effects and negative pressures, with evident spatial and temporal variability. Urbanization and economic development promote forest expansion in certain areas, while contributing to the reduction in farmland and shrub–grass lands. Significant variations are influenced by factors such as the urbanization rate, the agricultural population, the industrial composition, and fiscal revenue. This study enhances the in-depth understanding of the relationship between the spatiotemporal dynamics of green spaces and socially driven mechanisms, offering significant insights for sustainable urban planning and landscape management and harmonizing urban agglomeration development. Full article

Understanding the complex relationship between ESSD and human well-being is of paramount significance to protecting regional ecology, enhancing human well-being and achieving sustainable development. We take the Yangtze River Economic Belt as an example and use multi-source data to analyse land use and cover change, as well as the spatiotemporal evolution of ESSD and human well-being. We explore and reveal the coupling coordination relationship between ESSD and human well-being. The results show that from 2000 to 2020, the overall trend in ESs in the region improved significantly, and the supply notably increased, whereas the demand growth rate was even more pronounced. The supply–demand ratio for water yield and soil conservation showed little change, with variations of <10%. However, the supply–demand ratio for carbon sequestration declined significantly by 41.83%, whereas that for food supply increased notably by 42.93%. The overall spatial pattern in ESSD presented a mismatch, which was characterised by ‘low supply and high demand in the eastern region and high supply and low demand in the western region’. Overall, human well-being remained stable and was in line with the level of socio-economic development, thereby exhibiting a distinct trend of well-being ‘polarisation between the rich and poor’. Well-being was higher in the eastern and central urban agglomerations and lower in the western plateau and mountainous areas. Over 20 years, the degree of coupling coordination between ESSD and human well-being increased by 0.0107, and the coupling level gradually transitioned from moderate imbalance to moderate coordination. Spatially, Hubei Province, Chongqing Municipality and the Yangtze River Delta were the main ‘high–high’ agglomeration areas, whereas the Sichuan Basin and the Yunnan-Guizhou Plateau were the main ‘low–low’ agglomeration areas. Based on these findings, we propose the following management recommendations for the Yangtze River Economic Belt and other related great river economic belts: optimise land use structure, rationally allocate natural resources, strengthen regional and external connections and promote regional coordinated development, enhance the implementation of policies for ecological and environmental protection, establish regional ecological compensation mechanisms and coordinate ecological protection in a full scope and focus on harmonising human–land relationships, build a multi-stakeholder collaborative governance mechanism and promote regional ecological protection and the elevation of human well-being. Full article

The acceleration of urbanization has led to an increase in urban expansion and population density, exacerbating the urban heat island (UHI) effect. Moreover, the phenomenon has a significant impact on urban ecological environments and human health. Consequently, mitigating the UHI effect and enhancing the ecological environment is crucial. However previous research has primarily focused on individual cities or regional scales, with few studies analyzing all cities within urban agglomerations. This paper conducts a fine-grained spatiotemporal analysis of surface urban heat island (SUHI) effects in the Central Yunnan City Cluster from 2000 to 2021 using Landsat satellite data. We calculate the surface urban heat island intensity (SUHII) for 44 cities at the county or district level and discuss the quantitative estimation of overall SUHII changes and driving factors in the Central Yunnan City Cluster. Our findings are as follows: 1. Small cities also exhibit UHI effects, with a 75.4% probability of occurrence in the Central Yunnan City Cluster from 2000 to 2021, resulting in an overall decrease in SUHII of 1.21 °C. 2. The temperature increase rate in urban extension areas and suburban areas is faster than that in urban central areas, which is the main reason for the decreasing trend of SUHII. 3. Land use change inhibits the weakening of the SUHI effect, and population change contributes to the formation of this phenomenon. Additionally, the methods and results of this study can provide reasonable and effective insights for the future development and planning of the Central Yunnan City Cluster, thus promoting urban sustainable development. Full article

Exploring the spatio-temporal differentiation characteristics and coupling coordination relationship of the composite ecosystem of urban agglomerations is of great significance for promoting the synergistic sustainable development and integration construction of urban agglomerations. This paper is based on LUCC (Land Use and Land Cover Change) data, a DEM (Digital Elevation Model), and temperature, precipitation, and other multi-source data, using the central Yunnan urban agglomeration as an example and constructing a multi-dimensional evaluation index system highlighting development quality and efficiency. The entropy weight method was first used to determine the comprehensive weights to evaluate the regional economic and social development level. Then, the InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) model was used to quantitatively calculate and analyze the spatial and temporal evolution characteristics of the four key ecosystem services, evaluating the spatio-temporal evolution characteristics of the natural subsystem. The coupling coordination model was used to quantitatively analyze the evolution of the coupling coordination of the composite ecosystems in the central Yunnan urban agglomeration during the period of 2010–2020, and to reveal its development law. The results show the following: ➀ During the study period, the socio-economic subsystems in the central Yunnan urban agglomeration demonstrated an outward radiative growth from Kunming City, marked by underdeveloped sub-centers and prevalent low-level areas. ② Trends in ecosystem services varied, with water and soil conservation showing fluctuating increases, carbon sequestration remaining stable, and habitat quality declining. The critically important integrated ecosystem services zone of the natural subsystem is mainly located in the northeastern region and southwestern edge of the study area. ③ In 2020, the coupling coordination degree of the composite ecosystem was 0.9492. This showed that economic, social, and ecological subsystems are highly coupled, with consistent overall development trends and strong interactions. ④ The increase in the degree of harmonization amounted to 7.82%, with lagging subsystems varying in the degree of harmonization in subregions. This study can provide a scientific foundation for the development of policies for the Central Yunnan urban agglomeration, promoting regional sustainable development and optimizing the spatial pattern of the national territory. Full article

Integrative development is an effective way to enhance urban potential and implement resource-optimal relocation, especially in urban agglomeration regions. Conventionally, the evaluation of urban integration is usually studied from one aspect of urban interaction intensity or urban functional similarity, but considering both together can better reflect the integrative condition of urban agglomeration. This paper introduces the symbiosis theory into the exploration of urban integration. The production–living–ecological function is taken to analyze urban function, and the improved radiation model is adopted to measure urban interaction. Under the framework of symbiosis theory, we integrate urban function and urban interaction to indicate the integrative condition of urban agglomeration from a production–living–ecological aspect. Urban agglomeration in the Central Yunnan Urban Agglomeration is taken as the study area. The results show that (1) spatial variations occur in high-value areas with distinct functions. The east emphasizes production and living, while the west leans towards ecology. (2) Urban agglomeration is in its early developmental stages without stable symbiosis. Interactions among counties mostly show sporadic point symbiosis, lacking stability. It mainly radiates outward from the central area, with more stable interactions in high-value areas, often causing inter-city competition. (3) Urban agglomeration integration is generally low, with distinct high-value production and ecological areas. The central, eastern, and southern regions exhibit strong production and living interactions, while the west benefits from ecological interactions. These findings can offer some insights for informing relevant policies and fostering the integrated development of urban agglomerations. Full article

Analyzing vegetation cover provides a basis for detecting ecological and environmental health in urban areas. We analyzed the temporal and spatial changes in vegetation cover using NDVI data from the central Yunnan urban agglomeration (CYUA). The dimidiate pixel model (DPM) and intensity analysis were used to study changes at three levels: time intervals, category, and transition. Analysis of time series data from 1990–2020 using the Theil–Sen Median with Mann–Kendal test identified the overall trends. Geodetector explored the relationship between natural and human factors in vegetation cover change. The CYUA’s vegetation cover gradually decreases from west to east and south to north, with middle–high and high vegetation occupying over 55%. During 1990–2020, significant improvement was observed in the east and north regions, with an increase of 22.49%. The anthropogenic core area showed severe degradation with nearly 1.56% coverage. The transformation intensity of middle vegetation coverage was dominant from 1990–2010 but was replaced by middle–high vegetation coverage from 2010–2020. Meanwhile, high vegetation coverage became the most prominent gains target, and the conversion of middle–high to high vegetation showed a system tendency to exceed the average in absolute number and relative intensity. Spatial and temporal differences in vegetation cover were mostly affected by land cover (q = 0.4726, p < 0.001), and the most influential topographic factor was the slope (q = 0.1491, p < 0.001). The impact of human activities has increased to 16%, double that of 2000. The CYUA’s vegetation cover improved more than it degraded, but required site-specific forest management due to human activities. Full article

The central Yunnan urban agglomeration represents a typical urban cluster in the southwestern region of China. The swift urbanization and land use changes in this region pose a severe threat to the ecosystem. A thorough assessment of the landscape ecological risk in the central Yunnan urban agglomeration holds paramount importance for devising effective risk management strategies and sustainable, high-quality development plans. This study utilizes long-term land-use raster data for six time periods (1995, 2000, 2005, 2010, 2015, and 2020) in the Central Yunnan urban agglomeration. Using GIS technology, a landscape risk index model is constructed, and a comprehensive assessment of landscape ecological risks in the Central Yunnan urban agglomeration is conducted using the 5 km × 5 km grid analysis method and Kriging interpolation. The results indicate that, between 1995 and 2020, the Central Yunnan urban agglomeration was dominated by forest land, grassland, and cultivated land as the primary land-use types. Forest land covered over 48% of the total area, while grassland and cultivated land accounted for more than 26% and 18%, respectively. Notably, construction land underwent a significant increase, mainly due to conversions from cultivated land, forest land, and grassland. Over a span of 25 years, the study area has experienced a continual rise in landscape ecological risk. The landscape ecological risk was mainly characterized by medium, higher, and high ecological risk. Grassland predominated in areas with medium levels of ecological risk, while cultivated land and construction land were predominant in regions with higher and high levels of ecological risk. Spatially, regions with lower ecological risk were primarily distributed in the Chuxiong Yi Autonomous Prefecture, whereas areas with higher and high levels of ecological risk were concentrated in Qujing City and Kunming City. The spatial aggregation patterns of landscape ecological risk in the Central Yunnan urban agglomeration featured “high–high” (H–H) and “low–low” (L–L) clusters, both displaying an initial increase followed by a decrease. The primary factors contributing to the rise in the landscape ecological risk index were identified as urban expansion, population growth, ecological fragmentation, and vegetation destruction. The study’s outcomes can offer valuable insights for optimizing land resources and promoting sustainable development in the Central Yunnan urban agglomeration. Full article

The process of urbanization alters the distribution of land use and gives rise to certain climatic modifications that have a direct influence on vegetation phenology. Mountainous areas have a fragile biological environment, and vegetation phenology is relatively sensitive to urbanization. However, there is a paucity of research on the impact of urbanization in mountainous areas on vegetation phenology. The Urban Agglomeration of Central Yunnan (UACY) is located on the Yunnan–Guizhou Plateau in China. This study explored the vegetation phenological changes in different terrains from 2001 to 2020 in the UACY based on remote sensing data. Using the dynamic gradient method, we examined the response of vegetation phenology to urbanization from three aspects: urban–rural gradient, urbanization intensity (UI), and population density. The results showed that landform has a significant impact on SOS (start of growing season), with a topographic relief difference of 200 m acting as the dividing line. The findings derived from the dynamic gradient analysis indicate that UI has the most significant effect. SOS advances by 5.77 days (R² = 0.96), EOS (end of growing season) advances by 2.30 days (R² = 0.83), and LOS (length of growing season) lengthens by 2.59 days (R² = 0.87) for every 10% increase in UI. This study has the potential to serve as a valuable resource for future urban planning and administration in the UACY. Additionally, it could provide decision-making support for the development of mountainous urban agglomerations in ecological environments. Full article

Green spaces are an essential aspect of building an eco-livable city and play an important role in building for eco-livability in the central Yunnan urban agglomeration. However, there are relatively few studies evaluating the eco-livability of green spaces. The establishment of a green-space eco-livability assessment system may help researchers to analyze the eco-livability of urban green spaces more effectively. To address this research gap, we constructed an ecological livability-evaluation index system for green spaces that incorporates three determinants—economic development, social life, and the ecological environment—using the green spaces of the urban agglomeration in central Yunnan as a case study. We used the entropy method to calculate the suitability for ecological livability of the green spaces in each district and county in the central Yunnan urban agglomeration for 2010, 2015 and 2020. We used the spatial autocorrelation analysis function of ArcGIS 10.8 software to explore the spatial clustering characteristics of the suitability for ecological livability of green spaces in the central Yunnan urban agglomeration. The results showed that, from 2010 to 2020, the suitability for ecological livability of green spaces of the 49 districts and counties in the central Yunnan urban agglomeration increased in some districts and decreased in others. The spatial characteristics were high in the central districts and counties and low in the peripheral districts and counties. The spatial characteristics of the suitability of the target layers for economic development and ecological-environment target were consistent with the overall suitability. Through a spatial autocorrelation analysis, we observed that the suitability of green spaces for ecological livability had a positive spatial correlation and demonstrated significant spatial clustering. In this study, we propose recommendations to improve the suitability for ecological livability of green spaces from two dimensions of government policy and urban development, using a combination of the three target layers. The results of the study provide a reference for decision-making in the construction of eco-livable cities in the central Yunnan urban agglomeration. Full article

This study used a two-stage network data envelopment analysis model to measure the water use efficiency of 108 cities in the Yangtze River Economic Belt in the initial water use and wastewater treatment phases from 2009 to 2019. We divided the urban water use efficiency of six significant urban clusters in the Yangtze River Economic Belt using the Dagum Gini coefficient. We also tested the convergence characteristics of urban water use efficiency in six significant urban clusters in the Yangtze River Economic Belt using convergence and convergence kinds. According to this report, the Yangtze River Economic Zone’s cities often have low levels of water use efficiency, which is primarily due to ineffective wastewater treatment. The 108 cities in the Yangtze River Economic Zone are divided into four types based on the average values of water use efficiency in the initial use and wastewater treatment phases; the highest number of cities are in the double-low category, with low average values of water use efficiency in the initial use and wastewater treatment phases. During the study period, spatial differences in urban water use efficiency in the Yangtze River Economic Zone narrowed, with the differences stemming mainly from hyperdensity, followed by intra- and inter-regional differences. Meanwhile, there is convergence in urban water use efficiency in the Yangtze River Economic Belt, significant β convergence in the urban agglomerations of the Yangtze River Delta, Jianghuai, middle reaches of the Yangtze River, Chengdu–Chongqing, and Central Yunnan, and insignificant β convergence in the Central Qian urban agglomeration. After considering control factors, such as industrial structure, financial development level, environmental regulation, economic development level, and science and education development level, the water use efficiency of the six major urban clusters in the Yangtze River Economic Belt converges faster, but the influence of these control factors on the water use efficiency of each urban cluster is heterogeneous. Research results have reference value for the development of improvement strategies on differentiated urban water use efficiency in the Yangtze River Economic Belt. By measuring the regional differences in water use efficiency of urban agglomerations in the Yangtze River Economic Belt and clarifying their convergence mechanism, it provides a basis for analyzing the spatial pattern of water use efficiency in urban agglomerations and has reference value for formulating differentiated urban water use efficiency improvement strategies in the Yangtze River Economic Belt. Full article