Search Results (147)

In the context of pursuing high-quality development, the coupling and coordination of the ecosystem and economy has become the fundamental goal and inevitable choice for achieving the sustainable development of urban agglomerations. Based on remote sensing and statistical data for the Pearl River Delta (PRD) region from 2005 to 2020, in this paper, we construct an index system of the ecological and economic levels to assess the ecosystem service value (ESV). We use the equivalent factor method, entropy method, coupling coordination model, and relative development model to systematically grasp the spatial pattern of the levels of the two variables, analyse and evaluate their spatial and temporal coupling and coordination characteristics, and test the factors influencing their coupling and coordination using the geographical and temporal weighted regression (GTWR) model. The results show that ① the ESV in the PRD exhibited a fluctuating decreasing trend, while the level of the economy exhibited a fluctuating increasing trend; ② the coordination degree of the ESV and economy in the PRD exhibited a fluctuating increasing trend, and the region began to enter the basic coordination period in 2007; ③ in terms of the spatial distribution of the coordination degree, there was generally a circular pattern, with the Pearl River Estuary cities as the core and a decrease in the value towards the periphery; ④ the coordinated development model is divided into balanced development, economic guidance, and ESV guidance, among which balanced development is the major type; ⑤ the results of the GTWR reveal that the influencing factors exhibited significant spatial–temporal heterogeneity. Government intervention and openness were the dominant factors affecting the coordination, and the normalised difference vegetation index was the main negative influencing factor. Full article

Urbanization is growing at a rapid pace, and this is being reflected in the rising energy consumption from fossil fuels, which is contributing significantly to greenhouse gas impacts and carbon emissions (CE). Aiming at the problems of the time delay, inconsistency, uneven spatial coverage scale, and low precision of the current regional carbon emissions from energy consumption accounting statistics, this study builds a precise model for estimating the carbon emissions from regional energy consumption and analyzes the spatio-temporal characteristics. Firstly, in order to estimate the carbon emissions resulting from energy consumption, a fixed effects model was built using data on province energy consumption and NPP-VIIRS-like nighttime lighting data. Secondly, the PRD urban agglomeration was selected as the case study area to estimate the carbon emissions from 2012 to 2020 and predict the carbon emissions from 2021 to 2023. Then, their multi-scale spatial and temporal distribution characteristics were analyzed through trends and hotspots. Lastly, the influence factors of CE from 2012 to 2020 were examined with the OLS, GWR, GTWR, and MGWR models, as well as a ridge regression to enhance the MGWR model. The findings indicate that, from 2012 to 2020, the carbon emissions in the PRD urban agglomeration were characterized by the non-equilibrium feature of “high in the middle and low at both ends”; from 2021 to 2023, the central and eastern regions saw the majority of its high carbon emission areas, the east saw the region with the highest rate of growth, the east and the periphery of the high value area were home to the area of medium values, while the southern, central, and northern regions were home to the low value areas; carbon emissions were positively impacted by population, economics, land area, and energy, and they were negatively impacted by science, technology, and environmental factors. This study could provide technical support for the long-term time-series monitoring and remote sensing inversion of the carbon emissions from energy consumption in large-scale, complex urban agglomerations. Full article

With the increase in human activities and the acceleration of urbanization, over-exploitation of natural resources has led to a decline in ecosystem services (ESs), subsequently affecting the achievement of sustainable development goals (SDGs). As the key ecological zone of Qinghai-Tibet Plateau, the stability and enhancement of ESs in the Hehuang Valley are crucial for achieving SDGs and biodiversity conservation. This study quantifies nine SDGs for the Hehuang Valley in the last twenty years. Four ecological models were utilized to compute key ESs: net primary productivity (NPP), water yield, soil retention, and sand fixation. Panel data were analyzed using a coupling coordination model to quantify the relationship between ESs and sustainable development level (SDL) in each county. Additionally, the Geographically and Temporally Weighted Regression (GTWR) model was employed to examine the correlation between ESs and SDL. The results indicate the following: (1) During the period, NPP and water yield first increased and then decreased. The capacity for soil retention and sand fixation showed an overall increase, highlighting substantial variability among counties in their ability to deliver these ESs. (2) The SDL of counties in the Hehuang Valley increased, with Xining City showing slightly higher SDL than other counties. (3) The overall coupling coordination degree among NPP, water yield, soil retention, sand fixation, and SDL in the Hehuang Valley exhibited an upward trend in the last twenty years. SDL demonstrated the highest coordination degree with NPP, followed by soil retention, water yield, and sand fixation. (4) Most counties in the Hehuang Valley exhibited a lag in SDL relative to NPP, water yield, and soil retention in the last twenty years. In the early stage, sand fixation and SDL were primarily lagging in SDL, while in the late stages, sand fixation lagged behind SDL. (5) During the period, there was an increasing negative correlation observed between the four ESs and SDL. The positive contribution of NPP and sand fixation in some counties gradually shifted to a negative effect, and the negative effect of water yield and soil retention on SDL intensified. The impact of human activities on ecosystem function hindered local SDL. This study offers scientific theoretical backing and practical recommendations for promoting SDL and biodiversity conservation in the Hehuang Valley. Full article

The urban–rural imbalance, a social problem shared globally, is seeing a turnaround as a result of changes in production patterns. Tourism can not only provide employment but also drive the development of related industries, which is an effective measure to solve the urban–rural dichotomy. Against this background, we take the Beijing-Tianjin-Hebei (BTH) urban agglomeration as a sample, uses new urbanization and rural revitalization as a criterion for measuring urban and rural development, and quantifies the degree of urban–rural coordinated (URC) value in the BTH urban agglomeration from 2010 to 2019 by using the coupled coordination degree model. After that, the geographically and temporally weighted regression (GTWR) model is used to analyze the impact of tourism on the URC. The results show that: (1) there are large gaps within the BTH urban agglomeration in terms of urban and rural development, and there may be a threshold effect for the URC; (2) the impact of tourism on the URC shows spatiotemporal heterogeneity and the highest degree of diversity is high-quality intangible cultural heritage resources; (3) the density of highways exerts a negative impact on the URC. Finally, based on the findings, tourism is as an anchoring point to provide policy guidance for sustainable urban–rural development. Full article

To objectively evaluate the road traffic safety levels across different provinces in China, this study investigated the spatiotemporal heterogeneity characteristics of macro factors influencing road traffic accidents. Panel data from 31 provinces in China from 2009 to 2021 were collected, and after data preprocessing, traffic accident data were selected as the dependent variables. Population size, economic level, motorization level, highway mileage, unemployment rate, and passenger volume were selected as explanatory variables. Based on the spatiotemporal non-stationarity testing of traffic accident data, three models, namely, ordinary least squares (OLS), geographically weighted regression (GWR), and geographically and temporally weighted regression (GTWR), were constructed for empirical research. The results showed that the spatiotemporal heterogeneity characterizing the macro factors of traffic accidents could not be ignored. In terms of impact effects, highway mileage, population size, motorization level and passenger volume had positive promoting effects on road traffic accidents, while economic level and unemployment rate mainly exhibited negative inhibitory effects. In terms of impact magnitude, highway mileage had the greatest impact on traffic accidents, followed by population size, motorization level, and passenger volume. Comparatively, the impact magnitude of economic level and unemployment rate was relatively small. The conclusions were aimed at contributing to the objective evaluation of road traffic safety levels in different provinces and providing a basis for the formulation of reasonable macro traffic safety planning and management decisions. The findings offer valuable insights that can be used to optimize regional traffic safety policies and strategies, thereby enhancing road safety. Full article

Based on the DPSIR framework, this study constructed an evaluation index system to assess the sustainable development levels of the tourism eco-security system (TESS-SDL) present in the Chengdu-–Chongqing urban agglomeration and synthesized multi-dimensional analysis methods to explore its spatiotemporal evolution characteristics and driving factors to provide an important theoretical and practical basis for promoting the sustainable development of the regional tourism eco-security system. The results showed the following: (1) From 2011 to 2021, the regional TESS-SDL was generally at a medium level and showed a trend of steady growth. Although the gap between cities was widening year by year, the speed of the TESS-SDL exceeded the speed of the widening gap, promoting the coordinated development of the regional TESS-SDL. (2) The spatial spillover effect of the regional TESS-SDL was obvious; however, the siphoning effects of Chongqing and Chengdu were strong, and the demonstration effect was insufficient. (3) The dynamic evolution process of the TESS-SDL shows a strong self-locking effect. The risk of downward development (lower sustainability) is greater than the potential for upward development (higher sustainability) and is significantly influenced by neighboring cities. (4) In terms for assessing the driving factors, open-door and green-development policies show positive facilitating effects, while the positive influencing capacities of information technology, economic development, and tourism are moving toward having negative effects; the influencing effect of technological innovation has transitioned from positive to negative. Full article

Ecological zoning management aims to ensure ecological functions and improve environmental quality, serving as an essential means to optimize the development and protection of territorial space. However, comprehensive research on ecological zoning management that combines human needs with natural resources is still relatively scarce. In this study, we selected water yield (WY), food provision (FP), and carbon sequestration (CS) as the critical ecosystem services (ES) in China. An InVEST model, ecosystem services supply–demand index (ESI), random forest (RF), and geographically and temporally weighted regression (GTWR) were used to analyze the spatiotemporal characteristics and influencing factors of ES supply and demand, and the four-quadrant model was used to analyze the spatial matching patterns. The results showed that: (1) from 2005 to 2020, the supply and demand of WY, FP, and CS increased. Among them, WY, FP, and CS supply increased by 16.06%, 34%, and 22.53%, respectively, while demand increased by 5.63%, 12.4%, and 83.02%, respectively; (2) the supply of WY and CS follow a “high in the southeast and low in the northwest” pattern, while all of the demands exhibit a “high in the east and low in the west” pattern; and (3) the average ecosystem service supply–demand index (ESI) values for WY, FP, and CS in China are 0.45, 0.12, and −0.24, respectively, showing an overall upward trend. The study identified three dominant functional zones for WY, FP, and CS, and four classification management zones, including protection zones, conservation zones, improvement zones, and reconstruction zones. These research findings provide a scientific basis for future territorial space planning in China and the application of ecosystem service supply and demand in sustainable development. Full article

With global population growth and economic development, the sustainable utilization of arable land resources has become the key to guaranteeing food security and ecological balance. Eco-efficiency in cultivated land use (ECLU)has been increasingly emphasized as an important indicator of the coordinated development of agricultural production and the ecological environment. Studying ECLU in main grain-producing areas (MGPAs) is of great significance for realizing China’s food security guarantee, formulating and implementing scientific land use policies and measures, and safeguarding the long-term healthy development of agriculture. Based on provincial panel data of MGPA from 2008–2021, ECLU is calculated by the super-efficiency slacks-based measure model based on non-desired outputs (SSBM) and non-parametric kernel density estimation. The Dagum Gini coefficient decomposition model was used to explore the spatial non-equilibrium characteristics of ECLU in China, and the geographical and temporal weighted regression (GTWR) model was used to analyze the influencing factors of ECLU. The results showed the following: (1) ECLU in the MGPA showed a fluctuating upward trend, but the overall level was low. (2) In terms of regional disparity, the absolute difference in the development of ECLU among provinces showed a trend of “small-scale expansion followed by reduction”. (3) ECLU showed significant spatial imbalances, with notable internal disparities within the three basins. (4) The effects of economic development level and agricultural irrigation index on ECLU in the MGPA were positively correlated. Based on these findings, this paper suggests implementing region-specific and phased policies tailored to the natural resources and socio-economic conditions of different areas. The aim is to enhance the ecological environment, promote coordinated agricultural development, optimize regional growth, reduce agricultural disparities, and achieve sustainable development for both people and arable land. Full article

Rapid urbanization in the Songhua River Basin (SRB), a crucial ecological barrier in China and Northeast Asia, has led to the degradation of ecosystem service functions and a decline in their value, thereby posing a significant threat to regional ecological security. Clarifying the complex coupling coordination relationship between urbanization and ecosystem services (ESs) and identifying the spatiotemporal heterogeneity of their interactions will facilitate the high-quality and coordinated development of urbanization and ESs in the SRB. This study employed a systems approach, treating urbanization and ESs as overarching systems and delineating different aspects of urbanization and ecosystem service functions as subsystems within these systems. The spatiotemporal characteristics of urbanization and the ecosystem service value (ESV) in the SRB from 1985 to 2021 were revealed. The coupling coordination relationship and the spatiotemporal heterogeneity of the interactions between urbanization and ESs in the SRB at both the system and subsystem levels were analyzed using the coupling coordination degree (CCD) model and the spatiotemporal geographically weighted regression (GTWR) model. The findings indicated that during the study period: (1) The urbanization index of SRB rose from 0.09 to 0.34, while the ESV experienced a decrease from 2091.42 × 10⁷ CNY to 2002.44 × 10⁷ CNY. (2) The coupling coordination degree (CCD) between urbanization and ESs in the SRB at both the system and subsystem levels increased significantly, generally transitioning from the moderately unbalanced to the basically balanced stage. Areas with high CCD values were mainly distributed in ecological function areas and low-level urbanized areas, while areas with low CCD values were mainly distributed in grassland ecological degradation areas, ecologically fragile areas, resource-dependent old industrial cities, and highly urbanized areas. (3) The subsystems of urbanization had an overall negative impact on Ess, with varying trends, but the spatial distribution pattern of the interactions remained relatively stable. Conversely, the subsystems of ESs all exhibited a trend of initially strengthening and then weakening their negative impacts on urbanization, and the spatial distribution pattern was highly correlated with the spatial distribution pattern of ESV in the SRB. Full article

Exploring the carbon balance pattern from the perspective of urban spatial development pattern is an effective way to solve the urban carbon emissions reduction problem, promote high-quality economic development, and synergize the development of the regional “nature–economy” dual system. Taking 105 counties (districts) in Anhui Province as an example, based on the calculation of regional carbon balance and urban development characteristics in 2001, 2010, and 2019, we used the spatio-temporal leap model to analyze urban development characteristics and combined the GWTR model and geodetic probes to explore the spatial and temporal correlation between the carbon balance and urban development characteristics, as well as their influence mechanisms. The results of the study show that: (1) The carbon balance of the 105 counties in Anhui Province shows a general decline in the time axis, with a small recovery, and the spatial sequence decreases and then increases from the north to the south. (2) The urban structure of southeast Anhui Province and central Anhui Province is stable, and the development status is good, but the carbon balance is out of balance, the carbon emissions are much higher than the carbon sinks, and the urban structure of the mountainous areas of west Anhui Province and north Anhui Province is dynamic and coordinated, with the carbon balance in harmony. (3) The spatial development characteristics of the cities in Anhui Province have a negative impact on the carbon balance at the scale-area level and a positive impact at the functional structure level. Among them, the area of urban built-up area and the number of the largest urban patches have strong explanatory power for the carbon balance, and the number of the largest urban patches is the main driver of spatial heterogeneity in the carbon balance. (4) The carbon budget of Anhui Province under the influence of urban spatial development characteristics can be divided into four regions: the economic development–carbon balance lopsided area, the ecological protection–carbon balance surplus area, the urban agglomeration–carbon balance adjustment area, and the potential enhancement–carbon balance equilibrium area. Based on the results, urban development needs to strengthen the construction of urban functional zones, and when formulating low-carbon policies in provinces with uneven development, it is necessary to comprehensively analyze the differences in development between cities and build cities according to local conditions. Full article

Analyzing the change trend of urban green space (UGS) and exploring related driving forces can provide scientific reference for sustainable development in rapidly urbanizing areas. However, the spatial and temporal driving mechanisms of the drivers on UGS patterns at different scales are still not deeply understood. Based on the GlobeLand30 land cover data, nighttime lighting data and spatial statistics from 2000 to 2020, this study analyzed the size, shape and diversity of UGS in Guangzhou at the urban level, gradient level and township level with multiple landscape indices. Diversity means the richness of UGS patch types. The selected indices include percent of landscape (PLAND), largest path index (LPI), landscape shape index (LSI), aggregation index (AI) and Shannon’s diversity index (SHDI). The spatiotemporal heterogeneity of the drivers was then explored using the spatiotemporal weighted regression (GTWR) method. Results showed the following: (1) During 2000−2020, the total amount of UGS in Guangzhou increased slightly and then decreased gradually. UGS was mainly transferred into artificial surfaces (lands modified by human activities). (2) The UGS landscape showed a non-linear trend along the urban–rural gradient and fluctuated more in the interval of 20–60% urbanization level. PLAND, LPI and AI decreased significantly in areas with higher levels of urbanization. LSI increased and SHDI decreased significantly in areas with lower levels of urbanization. At township level, the landscape indices showed significant spatial autocorrelation. They transformed from discrete changes at the edge and at the junction of the administrative district to large-scale aggregated change, especially in northern areas. (3) The size of UGSs was mainly influenced by natural factors and population density, but their shape and diversity were mainly influenced by socio-economic factors. More regular shapes of green patches were expected in higher urbanization areas. Population agglomeration positively influenced green space patterns in the northeastern and southern regions (Zengcheng, Conghua and Nansha). Meanwhile the negative influence of urban expansion on the green space pattern in the central and southern regions decreased over time. This study contributes to an in-depth understanding of how the key factors affect the different changes of UGS with time and space and provides methodological support for the long-term zoning planning and management of UGS. Full article

China’s urban–rural dichotomy has resulted in a widening gap between urban and rural areas, posing significant challenges to rural development. This study aims to investigate the spatio-temporal differentiation and driving mechanisms of rural industry integration within the Chengdu–Chongqing Economic Circle in China. Using panel data from 2011 to 2020, we employed the entropy weight TOPSIS method to construct a comprehensive index that charts the evolution of rural industry integration across various districts and counties. Additionally, we utilized fixed-effect and spatio-temporally weighted regression models to analyze the underlying driving forces behind this integration. Our findings reveal a dynamic and varied landscape of rural industry integration, with different levels of depth and breadth across various subsystems. Spatially, we observed a transition from a dispersed to a more concentrated agglomeration pattern within the Chengdu–Chongqing Economic Circle. This shift suggests a diffusion effect emanating from core metropolitan areas, as well as an attracting force exerted by adjacent metropolitan circles. In terms of drivers, market demand, openness level, financial development, policy support, and agricultural insurance breadth significantly contribute to rural industry integration. However, technological progress and rural human capital exhibit a weaker correlation. Notably, our models identified pronounced spatial–temporal heterogeneity among these influencing factors, highlighting a nuanced and dynamic relationship between them. Overall, our study emphasizes the crucial role of rural industry integration in bridging the urban–rural divide and fostering sustainable agricultural development and rural revitalization. The insights gained from this research provide valuable guidance for policymakers and stakeholders seeking to optimize rural development strategies and unlock the potential of integrated rural industries. Full article

The rise of ride-hailing services presents innovative solutions for curbing urban carbon emissions, yet poses challenges such as fostering fair competition and integrating with public transit. Analyzing the factors influencing ride-hailing emissions is crucial for understanding their relationship with other travel modes and devising policies aimed at steering individuals towards more environmentally sustainable travel options. Therefore, this study delves into factors impacting ride-hailing emissions, including travel demand, land use, demographics, and transportation networks. It highlights the interplay among urban structure, multi-modal travel, and emissions, focusing on network features such as betweenness centrality and accessibility. Employing the COPERT (Computer Programme to Calculate Emissions from Road Transport) model, ride-hailing emissions are calculated from vehicle trajectory data. To mitigate statistical errors from multicollinearity, variable selection involves tests and correlation analysis. Geographically and temporally weighted regression (GTWR) with an adaptive kernel function is designed to understand key influencing mechanisms, overcoming traditional GTWR limitations. It can dynamically adjust bandwidth based on the spatio-temporal distribution of data points. Experiments in Shenzhen validate this approach, showing a 9.8% and 10.8% increase in explanatory power for weekday and weekend emissions, respectively, compared to conventional GTWR. The discussion of findings provides insights for urban planning and low-carbon transport strategies. Full article

As a result of rapid urbanization in China, the spatial restructuring of towns and cities has significantly impacted urban compactness. The study of the spatio–temporal characteristics and driving mechanisms of urban compactness in central China is a strategic imperative and conducive to promoting regional sustainable development that is based on easing the contradiction between land resource supply and demand and reducing energy consumption. Therefore, this study focused on 80 prefecture-level cities in central China, utilizing barycenter model and GTWR model, among others, to analyze the spatio–temporal evolution pattern of urban compactness from 2006 to 2020 and its driving factors, with the aim of uncovering the intrinsic mechanisms behind enhancing urban compactness in the area. The results show the follows: (1) The urban compactness in central China has generally shown an upward trend, with a pronounced spatial clustering around provincial capital cities and the spatial changes in compactness predominantly concentrated in the north–south direction. (2) Various factors have influenced urban compactness, where government intervention and population aggregation present as bi-directional driving factors, while the effective use of land resources and high-quality industrial development, among others, present as positive driving factors. The spatio–temporal heterogeneity and agglomeration features of each driving factor are significant. (3) Further analysis indicates that the effective use of land resources is the primary factor in enhancing urban compactness, followed by technology. Therefore, we should adhere to the concept of compact cities and gradually promote the compactness of cities in central China based on the impact of the driving factors. Full article

Green and low-carbon use of urban land (GLUUL) and high-quality economic development (HED) are two closely linked and mutually reinforcing systems, and their coordinated development is of great theoretical and practical significance to the realization of green and sustainable urban development. Based on theoretical analysis, this paper used data from 2005 to 2020 to measure GLUUL efficiency and HED level and their coupling coordination degree (CCD) successively of 282 cities in China, and then analyzed in-depth the main factors affecting CCD and its spatial–temporal heterogeneity using the GTWR model. This study found that (1) GLUUL efficiency and HED levels are increasing with different trends, and the development is unbalanced. High-value cities in the two systems show a staggered distribution pattern. (2) The CCD of the two was dominated by primary and intermediate coordination types, and the overall became increasingly coordinated, with the “intermediate coordination—advanced development” type having the highest representation. (3) There is a gradual convergence of CCD spatial differences, showing an overall spatial distribution pattern that is “high in the northwest and southeast, low in the central area”. (4) The influence degree and direction of different factors on CCD are distinguishing. The positive impact of industrial structure upgrading (Isu) is obviously greater than other factors, which has the strongest effect on the industrial corridor along the Yangtze River and the Beijing–Tianjin–Hebei region. The findings can offer insightful recommendations for promoting sustainable development in China and similar developing countries and regions. Full article