Abstract:Urban agglomeration in the middle reaches of the Yangtze River is key to the rise of central China, and an important engine for the high-quality development of the Yangtze River economic belt. Research on urban agglomeration in the middle reaches of the Yangtze River focuses mainly on economic development, ecological environment, and innovation. Few studies focus on evaluation combining development levels. This study uses the entropy weight TOPSIS method to build an urban high-quality development level indicat… Show more
“…For instance, Li et al proposed connotation of HQD of city clusters based on the basic comprehension of Chinese-style modernization and measured the HQD of 19 city clusters by using the entropy weight CRITIC method [9]. Xie et al uses the entropy weight TOPSIS method to build an urban HQD level indicator system, comprehensively measuring the high-quality development level of 31 cities in the middle reaches of the Yangtze River and analyzing the evolution of spatial distribution and autocorrelation [44]. Tu et al assessed the HQD level of the Chengdu-Chongqing urban agglomeration from the perspective of spatial structure, scale, and urban connection [45].…”
The concept of high-quality development (HQD) is characterized by its emphasis on efficiency, equity, and environmental sustainability. In the context of China’s new urbanization development, the metropolitan area plays a crucial role in facilitating and sustaining HQD. This study focuses on the Changchun Metropolitan Area (CCMA) as a case study to measure the efficiency of high-quality development (HQDE) at the county level using the super-efficiency SBM model and spatial autocorrelation model. Additionally, we examine the spatio-temporal distribution characteristics of HQDE in terms of economy, innovation, coordination, greenness, openness, and sharing (EICGOS). The main findings are as follows: (1) The HQDE of the CCMA ranges from 0.7 to 0.8 with an initial rapid increase followed by a gradual decline; however, there are notable variations among different counties. (2) Regarding spatial structure within the metropolitan area, highest efficiency is observed in the half-hour living circle followed by the 2-h accessibility circle while lowest efficiency is found in the 1-h commuting circle. Over time, there is a declining trend in efficiency within core leading areas. (3) In terms of dimensions, CCMA demonstrates the highest level of economic development efficiency (EDE), whereas green development efficiency (GDE) exhibits lower levels compared to other dimensions. Furthermore, development efficiencies across all dimensions show a decline over time. (4) Spatially distributed patterns reveal significant agglomeration areas for HQDE within the CCMA region. High-high agglomeration areas are predominantly concentrated in the central region of Changchun and southern region of Liaoyuan while low-low agglomeration areas primarily exist in northwest Songyuan and specific counties within Changchun. To attain HQD of the CCMA, it is advisable to bolster the economic scale of the central city, mitigate developmental disparities between counties and cities, and expedite green transformations in old industrial cities. These findings offer a valuable point of reference for optimizing resource allocation at the metropolitan level and devising strategies to foster regional HQD.
“…For instance, Li et al proposed connotation of HQD of city clusters based on the basic comprehension of Chinese-style modernization and measured the HQD of 19 city clusters by using the entropy weight CRITIC method [9]. Xie et al uses the entropy weight TOPSIS method to build an urban HQD level indicator system, comprehensively measuring the high-quality development level of 31 cities in the middle reaches of the Yangtze River and analyzing the evolution of spatial distribution and autocorrelation [44]. Tu et al assessed the HQD level of the Chengdu-Chongqing urban agglomeration from the perspective of spatial structure, scale, and urban connection [45].…”
The concept of high-quality development (HQD) is characterized by its emphasis on efficiency, equity, and environmental sustainability. In the context of China’s new urbanization development, the metropolitan area plays a crucial role in facilitating and sustaining HQD. This study focuses on the Changchun Metropolitan Area (CCMA) as a case study to measure the efficiency of high-quality development (HQDE) at the county level using the super-efficiency SBM model and spatial autocorrelation model. Additionally, we examine the spatio-temporal distribution characteristics of HQDE in terms of economy, innovation, coordination, greenness, openness, and sharing (EICGOS). The main findings are as follows: (1) The HQDE of the CCMA ranges from 0.7 to 0.8 with an initial rapid increase followed by a gradual decline; however, there are notable variations among different counties. (2) Regarding spatial structure within the metropolitan area, highest efficiency is observed in the half-hour living circle followed by the 2-h accessibility circle while lowest efficiency is found in the 1-h commuting circle. Over time, there is a declining trend in efficiency within core leading areas. (3) In terms of dimensions, CCMA demonstrates the highest level of economic development efficiency (EDE), whereas green development efficiency (GDE) exhibits lower levels compared to other dimensions. Furthermore, development efficiencies across all dimensions show a decline over time. (4) Spatially distributed patterns reveal significant agglomeration areas for HQDE within the CCMA region. High-high agglomeration areas are predominantly concentrated in the central region of Changchun and southern region of Liaoyuan while low-low agglomeration areas primarily exist in northwest Songyuan and specific counties within Changchun. To attain HQD of the CCMA, it is advisable to bolster the economic scale of the central city, mitigate developmental disparities between counties and cities, and expedite green transformations in old industrial cities. These findings offer a valuable point of reference for optimizing resource allocation at the metropolitan level and devising strategies to foster regional HQD.
“…The YRMRUA's level is currently recognized as national [19], it is situated in the central region of China, and it serves as a pivotal location within the Yangtze River Economic Belt [20,21]. With its natural waterway, it provides convenient access to the Yangtze River Delta urban agglomeration and the Chengdu-Chongqing urban agglomeration.…”
The Yangtze River Middle Reaches urban agglomeration (YRMRUA) is a typical representation of policy-oriented urban agglomeration in China. In this study, we analyze the morphological characteristics of the built-up area of the YRMRUA, which is the research object, and we try to clarify changes in its development and the supporting role of policies. First, we used satellite image data provided by Google Earth Engine for supervised learning to obtain images of the built-up area land needed by the research. Then, we adopted radius dimension, spatial expansion intensity, and standard deviation ellipse successively to explore the spatial morphological characteristics of the YRMRUA. The following conclusions are drawn: (1) The built-up area of the YRMRUA with significant fractal characteristics has formed two parts, with diffusion-type fractals forming within its boundary and cohesion-type fractals forming outside its boundary. In addition, the fractal dimension has exhibited a gradual decline as time has passed. (2) The YRMRUA has gradually stabilized at a low rate of expansion of 0.2% per year. From the perspective of the grid, the spatial expansion intensity presented breakthrough and expansion in the second and third stages, respectively. The hot spots of space expansion with 95% confidence gradually changed from a point-like shape to a ribbon-like shape. (3) The expansion pattern of the YRMRUA showed a tendency of “northwest–southeast”, and gradually moved towards equilibrium. (4) A policy impetus has limitations, and the stages of space shaping has resulted in spatial solidification and differentiation. In response, we put forward suggestions for the objects and ways of policy functions, in order to provide references for the development of policy-oriented urban agglomerations.
“…The urban-rural integration index is considered a dependent variable. Based on the connotation of urban-rural integration discussed above and previous studies analyzing the influencing mechanism of urban-rural integration [76][77][78][79], an evaluation indicator system has been established following the principles of integrity, scientific nature, and feasibility. Fully considering data availability and validity, three indicators were selected to measure the urban-rural integration level in various counties and regions in Chongqing, namely economic integration, population integration, and social integration.…”
Section: Variables and Data Source (1) Dependent Variablesmentioning
The transfer of land development rights (TDR) is a significant policy tool for advancing urban–rural integration. This study establishes an analytical framework to examine the influence mechanism of TDR on urban–rural integration, considering the flow of land, capital, and population factors. Furthermore, an indicator system is developed to evaluate urban–rural integration across economic, social, and population dimensions. Using panel data from Chongqing, China (2013 to 2019), this article adopts the global principal component analysis (GPCA) method and time-varying difference-in-difference (TV-DID) model to analyze the effects of the land quota trading project, known as the ‘Dipiao’ policy. The results show that TDR can effectively promote urban–rural integration, though with a four-year time lag. Heterogeneous effects of TDR on urban–rural integration are observed across different districts and counties, with the more pronounced promotion in areas characterized by low agricultural land value or high industrial land value. This study further analyzes the influence mechanism of TDR on urban–rural integration. It concludes with policy implications on improving TDR to promote urban–rural integration.
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