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For a long time, China's economic development has followed a policy-oriented development model and achieved remarkable results. In the North-East, however, things do not seem to be going as smoothly as they should. This study aims to investigate the impact of the new round of Northeast Revitalization Policy (NRP), initiated in 2014, on the industrial economy of the Central and southern Liaoning Urban Agglomeration. By employing Synthetic Difference-in-Differences (SDID) methodology we provide an evaluation of policy's effects on industrial structure, innovation efficiency, and industrial clustering. The results show that: first, in the short term, the policy has significantly promoted the transformation of the industrial structure. However, the long-term effects are less pronounced; second, the policy's impact on the comprehensive technical efficiency of the urban agglomeration is positive but statistically insignificant. Comparing the core cities with other cities in this urban agglomeration, the policy has not brought about a more remarkable increase; third, we reveal that the policy has significantly enhanced the industrial specialization clustering degree and reduced the industrial diversification clustering degree. The findings in this research highlight the importance of continually monitor and evaluate the impact of revitalization policies and adjust strategies. [ABSTRACT FROM AUTHOR]

The accurate extraction of urban residential space (URS) is of great significance for recognizing the spatial structure of urban function, understanding the complex urban operating system, and scientific allocation and management of urban resources. The traditional URS identification process is generally conducted through statistical analysis or a manual field survey. Currently, there are also superpixel segmentation and wavelet transform (WT) processes to extract urban spatial information, but these methods have shortcomings in extraction efficiency and accuracy. The superpixel wavelet fusion (SWF) method proposed in this paper is a convenient method to extract URS by integrating multi-source data such as Point of Interest (POI) data, Nighttime Light (NTL) data, LandScan (LDS) data, and High-resolution Image (HRI) data. This method fully considers the distribution law of image information in HRI and imparts the spatial information of URS into the WT so as to obtain the recognition results of URS based on multi-source data fusion under the perception of spatial structure. The steps of this study are as follows: Firstly, the SLIC algorithm is used to segment HRI in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) urban agglomeration. Then, the discrete cosine wavelet transform (DCWT) is applied to POI–NTL, POI–LDS, and POI–NTL–LDS data sets, and the SWF is carried out based on different superpixel scale perspectives. Finally, the OSTU adaptive threshold algorithm is used to extract URS. The results show that the extraction accuracy of the NLT–POI data set is 81.52%, that of the LDS–POI data set is 77.70%, and that of the NLT–LDS–POI data set is 90.40%. The method proposed in this paper not only improves the accuracy of the extraction of URS, but also has good practical value for the optimal layout of residential space and regional planning of urban agglomerations. [ABSTRACT FROM AUTHOR]

High-quality development is the primary task of comprehensively building a socialist, modern country, as well as the primary task of building urban agglomerations in China. Based on the five development concepts, this paper used the entropy method to measure the High Quality Development Index (HQDI) of the five major urban agglomerations. The results showed that the HQDI of the five major urban agglomerations shows a fluctuating upward trend. First, using the Dagum Gini coefficient to explore the sources of HQDI development differences in urban agglomerations, we found that the main source of HQDI differences in urban agglomerations was interregional differences, while intra-regional differences were not important. Second, kernel density estimation was used to test the dynamic evolution trend of HQDI within urban agglomerations. There was a polarisation phenomenon in the HQDI of urban agglomerations, such as the Pearl River Delta urban agglomeration and the Chengdu-Chongqing urban agglomeration. But overall, the degree of imbalance had decreased. Third, using geographic detectors to examine the driving factors of HQDI in urban agglomerations, we found that the main driving forces for improving HQDI in urban agglomerations were economic growth, artificial intelligence technology and fiscal decentralisation. All the interaction factors had greater explanatory power for the spatial differentiation of HQDI, which can be divided into two types: two-factor improvement and non-linear improvement. This study is conducive to improving and enriching the theoretical system for evaluating the high quality development of urban agglomerations, and provides policy references for promoting the high quality development of urban agglomerations. [ABSTRACT FROM AUTHOR]

There is a complex interaction between national land space and transportation. China is accelerating its strategy of building a strong transportation country and territorial spatial planning, which requires evaluating and strengthening the coordination relationship between transport and land space to promote development. Taking the Beijing–Tianjin–Hebei urban agglomeration in China as an example, this study analyze the high-speed transportation construction and land space development process, evaluates the coupling and coordination degree between high-speed transportation and land space, as well as the "development-protection" situation in the years 2000, 2010, and 2020 by means of the coupling and coordination model, spatial autocorrelation analysis, and GIS analysis. The result shows: (1) high-speed transportation construction and territorial space development have been active for a long time, and most of the cities have maintained a high level of increase in these two indicators. In terms of protection indicators, Tangshan and other coastal cities have been lagging behind for a long time without any improvement trend. (2) The coupling and coordination level between high-speed transportation and development is high, with slight weakening over time, with an average annual decrease of less than 0.09%. The change in the coupling coordination level with protection shows the wave dynamics of 'low-middle-low'. (3) In the future, high-speed transportation will have a significant impact on land space in the country for a long time. In this regard, it is suggested to: (1) promote the construction of high-speed transportation for network, systematic, and serial development; (2) accelerate the extension of the high-speed transportation advantages of the existing growth poles of Beijing and Tianjin; and (3) develop Shijiazhuang and Langfang as the new growth poles. This study will promote the integration of transportation and urban planning, which will contribute to the development of high-quality synergistic urban agglomerations around the world. [ABSTRACT FROM AUTHOR]

Intercity railways in urban agglomerations serve as critical transportation infrastructure, playing a key role in supporting and guiding the advancement of new urbanization in China. The functional orientation and technical standards of such railways have become focal areas of research within the industry. However, the current national railway technical standard system is insufficient to fully address the entire process of intercity railway construction and operation in urban agglomerations, particularly within the framework of "four network integration and interconnection". This study focused on the intercity railways in Jiangsu Province's urban agglomerations, with the goal of facilitating their integration into city centers and their operation as public transit systems. Based on their functional positioning and technical characteristics, and through comparisons with the national railway and urban rail transit standard systems, two major subsystems-engineering construction and transportation services-were constructed. Moreover, the system encompassed several key business areas, including foundation, surveying, design, construction, inspection, operation, management, and services. A standard framework, covering various specialized and thematic research areas, was established to guide the design, construction, equipment, inspection, and operational management of intercity railways in urban agglomerations. This framework aims to realize the vision of "unified planning, unified standards, coordinated operation, interconnection, seamless transfers, and one-ticket access." [ABSTRACT FROM AUTHOR]

The construction of urban agglomerations around Poyang Lake is an important starting point of the strategy for the improvement of central China, but the spatial agglomeration of industry and population brings great pressure to the ecological environment. It is of great practical value to explore the impact of rapid urbanization on the water use efficiency of important ecological functional areas. Considering the undesired output of industrial production, this paper adopts the SE-SBM model to measure industrial green water use efficiency, comprehensively considers different aspects of urbanization of the urban agglomeration around Poyang Lake, empirically tests its inhibiting or boosting effect on industrial green water use and explores its spatial spillover effect with the help of a spatial metrology model. The results show that (1) the industrial green water use efficiency of urban agglomerations shows an overall upward trend, and the efficiency value of central cities is significantly higher than that of non-central cities and continues to show a state of diffusion; (2) social urbanization, environmental urbanization, and balanced urbanization can significantly improve industrial green water use efficiency, while industrial urbanization or industrialization inhibits the improvement in water use efficiency; (3) considering the spatial spillover factor, there are significant positive local effects between population urbanization and balanced urbanization, and significant positive spatial spillover effects between industrial urbanization and environmental urbanization; (4) the original model can pass the significance test by replacing the output-oriented water use efficiency with the input-oriented or non-oriented water use efficiency; the study area is extended to Jiangxi Province, and the impact of urbanization on industrial water use efficiency is basically consistent. We should adhere to the new type of urbanization that improves well-being and is friendly to the environment, rationally plan the industrial spatial pattern of urban agglomerations, adhere to the ecological and environmental threshold on undertaking industrial transfer, and promote the flow and sharing of green production factors. [ABSTRACT FROM AUTHOR]

High-speed rail is a high-standard railway system, which allows trains to operate at high speed. The railway play a crucial role in connecting urban agglomerations, which represents the highest form of spatial organization in the mature stage of urban development, bringing together cities of various natures, types, and scales in specific regions. This paper explores the impacts of high-speed rail and its expansion on industrial concentration and macroeconomic conditions in the period of 2000 to 2019. We use a well-known transportation policy as a natural experiment, utilizing geographic distance data to study the effects of high-speed rail and its expansion on industrial concentration and macroeconomic conditions in urban agglomerations. The results show that high-speed rail increases industrial concentration but leads to a reduction in macroeconomic conditions. Unlike previous studies in this field, we use distance variables to analyze how the expansion of high-speed rail affects macroeconomic conditions and industrial concentration through location advantages. The impacts of high-speed rails vary across urban and non-urban agglomeration cities, resource-based and non-resource-based cities, large and small cities, and eastern, central, and western regions. Our results are robust to the shocks from the global financial crisis, time lags, different distance dummy variables, dependent variables, and endogeneity issues. This study regards the opening up of high-speed rail as both improving air quality and reducing carbon emissions through substituting for urban and aviation transport. Compared to traditional transport methods such as urban and air travel, the efficiency and environmental benefits of high-speed rail make it an important method for reducing greenhouse gas emissions. Consequently, the expansion of high-speed rail could support both economic development and environmental concerns, and it is playing a crucial role in transportation selection for advancing low-carbon economic goals. [ABSTRACT FROM AUTHOR]

In the face of accelerating urbanization, Urban Green Spaces (UGS) have become vital for sustaining urban ecosystems and the health and well-being of urban residents. This study offers a comprehensive analysis of the growth rate of urban green space (GRUGS) across various regions in China over a two-decade period, highlighting the interplay between urban development, population dynamics, and ecological sustainability. The research meticulously examines the impacts of urban built-up area expansion, population growth, and air pollution on GRUGS. It categorizes 291 Chinese cities into 15 urban agglomerations and utilizes data on urban built-up areas, population, and PM2.5 levels from 2000 to 2020. The findings reveal a mixed picture: while some regions demonstrate a robust commitment to integrating green spaces within urban growth, evident in high GRUGS values, others struggle to preserve green spaces amidst rapid urban expansion and population surges. This study underscores the necessity of tailored urban planning strategies that are region-specific and the ongoing need for innovation in urban development to achieve ecological sustainability. The insights garnered are invaluable for policymakers and urban planners, stressing the indispensable role of green spaces in enhancing urban life quality and securing sustainable urban environments. [ABSTRACT FROM AUTHOR]

The aim of this paper is to explore whether and how urban road transport (URT) development affects haze pollution. One of the innovations of this paper is that URT development is measured by road accessibility with novel digital elevation model datasets, which have been used by few scholars. The endogenous problem caused by revere causality issue in the relationship between URT development and haze pollution is also considered. Based on the panel data of prefecture-level cities of Yangtze River Delta (YRD) region in China from 2011 to 2018, this paper uses long-lagged values of URT development as the instrumental variable, employing the two-stage least squares (2SLS) method. The study shows that URT development leads to an increase of haze pollution. Moreover, mechanism tests based on moderating and mediating models support the finding that decreasing haze pollution resulted from better connection effects, while rising agglomeration effects tend to bring about increasing haze pollution, and the latter effect is larger in magnitude than the former. Current URT development may have long-term negative consequences for livability of YRD cities, and urban decision makers should reconsider the effectiveness of the current road transport investment and construction. [ABSTRACT FROM AUTHOR]

Optimizing resource efficiency and mitigating climate change have become consensuses of human society. However, there is still a gap in assessing the carbon emission efficiency (CEE) and identifying the influence of various factors, especially in rapid urbanizing regions. In this paper, we built a stochastic frontier analysis model to assess CEE and conducted a case study in the Beijing–Tianjin–Hebei Urban Agglomeration (BTHUA), a typical area of collaborative development in China. A comprehensive influencing factor index was constructed to analyze and identify the key influencing factors of CEE. The results revealed that the average CEE among the 13 cities increased in volatility from 2000 to 2019. The average CEE in Langfang was lowest, while that in Tangshan was highest. The input-related factors had a negative effect on CEE, including carbon emissions per capita, employment per ten thousand people, total assets per capita, and energy intensity. GDP per capita, the urbanization level, and the proportion of the tertiary sector's GDP had positive impacts on CEE. Future policy formulation should focus on the transition from labor- and material-intensive industries to knowledge- and technology-intensive industries. All the results can contribute to achieving high-quality development and dual-carbon target of rapid-urbanizing areas. [ABSTRACT FROM AUTHOR]

The Hu-Bao-O-Yu urban area is a major source of carbon emissions in China. It is also a major source of energy exports and high-end chemicals in China. Reaching peak carbon emissions early is especially important for meeting the national peak goal. For urban areas that rely on natural resources, we need to make it clearer how carbon emissions and economic growth affect each other and slowly break the strong link between the two. Therefore, in this paper, based on the data on carbon emissions, the decoupling state and the driving mechanism of carbon emissions in the Hu-Bao-O-Yu City group are researched by using the Tapio decoupling model and GDIM method. A new decoupling index model is constructed by combining GDIM and the traditional decoupling model. The main findings are as follows: (1) The Hu-Bao-O-Yu urban agglomeration, Ordos City, Baotou City and Yulin City have significant growth trends in annual carbon emissions, with Yulin City being the most important carbon source for the Hu-Bao-O-Yu urban agglomeration and its economic contribution to carbon emissions of the whole urban agglomeration is the most efficient. (2) The decoupling of Hu-Bao-O-Yu, Huhhot City, Baotou City, and Ordos City is dominated by expansionary negative decoupling, whereas Yulin City has strong negative decoupling. (3) The Hu-Bao-O-Yu urban cluster mainly affects the carbon intensity of fixed asset investments and output carbon intensity, which is a key part of the carbon separation process. The energy scale and structure also play a part in this process over time. (4) Changes in GDP per capita are a bigger part of changes in carbon emissions in the Hu-Bao-O-Yu urban agglomeration. These changes also determine the direction for changes in carbon emissions in the Hu-Bao-O-Yu urban agglomeration. In the future, the Hu-Bao-O-Yu urban agglomeration needs to coordinate its economic growth. Ordos and Yulin need to speed up the optimisation and transformation of their energy structures. Baotou needs to push for the low-carbon transformation of its industries. Huhhot needs to do more research on carbon sequestration technology and spend more on environmental protection. This will make the Hu-Bao-O-Yu urban agglomeration a resource-saving urban agglomeration and improve its ability to reduce emissions. [ABSTRACT FROM AUTHOR]

Abstract The aim of this paper is to explore whether and how urban road transport (URT) development affects haze pollution. One of the innovations of this paper is that URT development is measured by road accessibility with novel digital elevation model datasets, which have been used by few scholars. The endogenous problem caused by revere causality issue in the relationship between URT development and haze pollution is also considered. Based on the panel data of prefecture-level cities of Yangtze River Delta (YRD) region in China from 2011 to 2018, this paper uses long-lagged values of URT development as the instrumental variable, employing the two-stage least squares (2SLS) method. The study shows that URT development leads to an increase of haze pollution. Moreover, mechanism tests based on moderating and mediating models support the finding that decreasing haze pollution resulted from better connection effects, while rising agglomeration effects tend to bring about increasing haze pollution, and the latter effect is larger in magnitude than the former. Current URT development may have long-term negative consequences for livability of YRD cities, and urban decision makers should reconsider the effectiveness of the current road transport investment and construction.

Urban agglomerations, emerging as pivotal spatial units, increasingly attract essential production factors—talent, technology, and capital—thereby transforming cities into innovation hubs. This study critically examined how productive service agglomeration, through the lens of agglomeration economies and externalities, acts as a catalyst for urban technological advancement. It investigated the spatial effects and underlying mechanisms by which productive service industry agglomerations impact urban technological innovation. Our findings reveal that both specialized and diversified agglomerations significantly enhance urban technological capabilities. However, diversified agglomerations might also negatively impact surrounding areas, revealing a complex spatial interplay. Importantly, while the aggregation of productive services boosts innovation by attracting R&D talent, it does not similarly influence the movement of R&D capital, thereby limiting further technological advancements. The effects of specialized and diversified agglomerations vary across different urban scales and regions. In China, although the productive service industry largely comprises lower-end sectors like finance, leasing, and business services, high-end tech industries remain underdeveloped, lacking robust growth momentum. This study underscores a critical gap in understanding the differential impacts of service industry agglomerations on urban innovation ecosystems and emphasizes the need for nuanced policy interventions to optimize these dynamics for sustainable urban and technological development. [ABSTRACT FROM AUTHOR]

Urban agglomeration development planning policy (referred to as planning policy in this paper) played a significant role in promoting regional economic development. However, an important issue is whether this planning policy promotes the efficiency of urban economic development. Therefore, based on panel data sets that cover 283 cities from 2007 to 2019, this paper used the planning policy that was approved by the China State Council as a quasi-natural experiment to investigate the effect of this planning policy on the efficiency of urban economic development. The results primarily found that the effect mechanisms of this planning policy on the efficiency of urban economic development contained two paths, which included the intermediary effects of industrial agglomeration and government action. In addition, the results showed that this planning policy played a leading role in influencing the efficiency of urban economic development with the concentration of secondary industries; however, implementing this planning policy did not improve the efficiency of urban economic development. In addition, the results show that the gap in economic development efficiency between cities was narrowing, and implementing this planning policy would facilitate the narrowing trend. Finally, to promote the high-quality development of the urban economy, this paper provides the targeted policy implications. [ABSTRACT FROM AUTHOR]

Abstract Transport accessibility is crucial for defining urban clusters and evaluating a region's centrality and connectivity. To foster equitable growth in urban conglomerates, it is crucial to understand the relationship between transport accessibility and regional development. This study introduces the concept of 'regional efficiency'—the effectiveness of converting regional inputs into outputs—determined via the super-efficiency Data Envelopment Analysis methodology, to assess the progression of regional development. Employing a combination of bivariate spatial autocorrelation and spatial regression analysis, this research elucidates the spatial dynamics between transport accessibility and regional efficiency, both at macro and micro levels. A binary Logit model identifies the factors affecting the Moran's I correlation between regional efficiency and transport accessibility. Based on the diverse urban characteristics within a single conglomerate, tailored development strategies are suggested. Focusing on the Yangtze River Delta Urban Agglomeration in China as a case study, four distinct spatial clusters—High–High (HH), Low–Low (LL), High–Low (HL), and Low–High (LH)—are identified, based on the local correlation between regional efficiency and transport accessibility. The findings reveal that regions with a High–High Moran's I correlation between road accessibility and regional efficiency predominantly located in the eastern sectors of the Yangtze River Delta, exhibiting effective regional efficiency. These regions are characterized by superior road accessibility, aligning well with their regional efficiency metrics. For air accessibility, cities classified under the HH category, including Shanghai and its neighboring cities, demonstrate a significant spatial correlation with regional efficiency. Population density and urban tier are key predictors of the significance of the Moran's I correlation between road accessibility and regional efficiency. In contrast, for air accessibility, these factors assume an inverse role. The identified cluster types (HH, LL, LH, and HL) are proposed as predictive indicators for the significance of the Moran's I relationship between air accessibility and regional efficiency.

The purpose of the article is to summarize the existing development experience of the Donetsk People’s Republic in the context of the administrative and territorial structure’s formation and improvement. The authors summarize the existing experience of administrative and territorial division, highlight the most characteristic features of possible transformations, and substantiate the need for early implementation of federal legislation into the current activities of state and local government bodies using logical, comparative, descriptive, and cartographic methods, as well as the method of analogies. The article identifies patterns of the administrative-territorial arrangement transformation in specific historical conditions, establishes cause-and-effect relationships between transformations in social production and changes in territorial development, distinguishes individual economic interest groups that generate contradictions in public relations, identifies the concentration factors for public production facilities in certain territories, visualizes the results of administrative boundaries administrative-territorial entities’ structure changes using maps. The article describes the chronology of transformations in the structure of administrative-territorial units over more than 100 years of Donbass’s existence in modern history. The Soviet period (1917–1991) is characterized by changes in administrative boundaries and the structure of administrative-territorial entities. The Ukrainian period (1991–2014) is distinguished by the intensified tension between local governments and central authorities, management. The period of statehood (2014–2022) is characterized by the completion of preparatory work preceding the entry of the Donetsk People’s Republic into the Russian Federation.

Introduction. The lack of unified approaches to (1) formation and development of agglomerations, (2) the regulatory legal framework for the methodological support of agglomeration processes, (3) the official conceptual framework in this area, (4) the assessment of agglomeration effects, (5) the approved methodology for delimiting agglomeration boundaries hinders the process of making informed decisions needed to solve a number of territorial, socio-economic, and transport problems arising in connection with the expansion of trans-regional integratory interactions between various constituent entities of the Russian Federation. In this regard, development of a border delimitation methodology for the St. Petersburg agglomeration is particularly relevant. The subject of the research is regulatory and methodological support for agglomeration processes. The goal is to develop a system of methodological support for creating and developing urban agglomerations within the framework of a well-balanced urban planning policy and legal framework of integratory processes in agglomerations.Materials and methods. The material for the study is the research focused on formation and development of agglomerations. Methods of system analysis and generalization of research results and practical work were applied to set the criteria for delimiting the boundaries of agglomerations. A methodology for delimiting the boundaries of the St. Petersburg agglomeration is proposed on the basis of analysis of research works of Russian scientists, results of practical research by St. Petersburg specialists, and special features of the St. Petersburg agglomeration.Results. The most complex theoretical and methodological problems of delimitation of the boundaries of the St. Petersburg agglomeration are identified; basic principles of formation and development of urban agglomerations are formulated to define the requirements for establishing boundaries; the main criteria for the delimitation of the St. Petersburg agglomeration are formulated, taking into account its specific features. A methodology for establishing the boundaries of the St. Petersburg agglomeration is proposed. Its main stages and research methods, used at each stage, are highlighted. The main problems of the legal support of formation and development of agglomerations are formulated.Conclusions. The research novelty and practical significance of the study result from the problems identified in the field of the regulatory support of agglomeration processes, which do not allow intensifying the development of agglomerations. The proposed methodology for establishing the boundaries of the St. Petersburg agglomeration is based on objective spatial development patterns of the two constituent entities of the Russian Federation and takes into account specific features of their interaction.

Land degradation due to mismanagement is widespread globally and may threaten the achievement of several UN Sustainable Development Goals. Yet the differences in land productivity degradation under various land management patterns (land sparing vs. land sharing) are poorly known. In this research, we used remote sensing data to develop a machine learning model for assessing the risk of land productivity degradation and interpreted the model using state‐of‐the‐art interpretable artificial intelligence techniques. In 2018, the risk level of land productivity degradation in the agricultural production space of the Yangtze River Delta urban agglomeration (YRD) was 0.230. More than half of the area was at low risk (68.19% of the area), mainly in mountainous and hilly areas. The degradation risk of the land sharing management pattern is lower than that of the land sparing pattern, but there are significant differences among provinces/municipalities. The four most influential factors for land productivity degradation in YRD were Normalized Vegetation Difference Index, nighttime light, elevation, and nitrogen deposition, which together explained 72.75% of the degradation risk. This study provides a methodological framework for land degradation governance in emerging urban agglomerations. It strongly recommends that policymakers explore locally appropriate land management patterns based on regional contexts. [ABSTRACT FROM AUTHOR]

Transport accessibility is crucial for defining urban clusters and evaluating a region's centrality and connectivity. To foster equitable growth in urban conglomerates, it is crucial to understand the relationship between transport accessibility and regional development. This study introduces the concept of 'regional efficiency'—the effectiveness of converting regional inputs into outputs—determined via the super-efficiency Data Envelopment Analysis methodology, to assess the progression of regional development. Employing a combination of bivariate spatial autocorrelation and spatial regression analysis, this research elucidates the spatial dynamics between transport accessibility and regional efficiency, both at macro and micro levels. A binary Logit model identifies the factors affecting the Moran's I correlation between regional efficiency and transport accessibility. Based on the diverse urban characteristics within a single conglomerate, tailored development strategies are suggested. Focusing on the Yangtze River Delta Urban Agglomeration in China as a case study, four distinct spatial clusters—High–High (HH), Low–Low (LL), High–Low (HL), and Low–High (LH)—are identified, based on the local correlation between regional efficiency and transport accessibility. The findings reveal that regions with a High–High Moran's I correlation between road accessibility and regional efficiency predominantly located in the eastern sectors of the Yangtze River Delta, exhibiting effective regional efficiency. These regions are characterized by superior road accessibility, aligning well with their regional efficiency metrics. For air accessibility, cities classified under the HH category, including Shanghai and its neighboring cities, demonstrate a significant spatial correlation with regional efficiency. Population density and urban tier are key predictors of the significance of the Moran's I correlation between road accessibility and regional efficiency. In contrast, for air accessibility, these factors assume an inverse role. The identified cluster types (HH, LL, LH, and HL) are proposed as predictive indicators for the significance of the Moran's I relationship between air accessibility and regional efficiency. [ABSTRACT FROM AUTHOR]

This paper analyzes the heterogeneous influence of economic networks on urban economic resilience capacity from different network characteristics, providing an innovative research perspective and theoretical framework for the economic resilience capacity of urban clusters. The urban economic elasticity is measured by multiple indicators and constructed economic network using night light data, the complex network approach was combined with spatial econometrics to analyse the contribution of economic network linkages and economic network locations to regional economic resilience capacity. The results show that: urban economic network linkage has a significant positive impact on urban economic resilience capacity, and the polycentric pattern of urban clusters has a driving effect on this impact; in contrast, the influence of urban network location on economic resilience capacity has an inverted u-shaped curve. Compared with non-smart cities, regions in smart cities are better able to promote urban economic resilience capacity through economic networks, and the impact of economic networks on regional economic resilience capacity has network external spillover effects beyond geographical distance, The results of the study infer that cities in urban agglomeration should rationalize network locations, and build a coordinated urban agglomeration network structure to enhance economic resilience capacity of the regional economy. [ABSTRACT FROM AUTHOR]

The sustainability of urban agglomerations is crucial to regional development worldwide, and the growth motivation of multiscale spatial structures is a worthy scientific problem in urban agglomerations. This study takes the urban agglomeration in the Yangtze River Delta as a case study to explore the growth motivation of multiscale spatial structures based on synergy theory. The growth of urban agglomerations mainly involves four stages: central city, urban communities, metropolitan area and urban agglomeration, each experiencing fluctuations in development factors during input, aggregation, diffusion and upgrading. At the same time, the upgrading of spatial synergistic relationships with the growth of urban agglomerations can be categorised into four types: internal, point-to-point, circle-to-circle and multicircle synergies. The theoretical contribution of this study lies in identifying that the upgrading of spatial synergistic relationships and the changes in development factor fluctuations collectively drive the growth motivation for urban agglomerations. These findings will help advance the academic research on spatial structure and urban planning policy in practice. [ABSTRACT FROM AUTHOR]

With the acceleration of urbanization, city clusters of different levels have emerged. They play a significant role in the process of carbon emissions. Based on the improved STIRPAT model and using the five most important city clusters in northern China as the research object, this study investigates carbon emissions (carbon emissions refer to CO2 emissions) from 2005 to 2021 and the urbanization factors that affect carbon emissions. The study found that energy urbanization has the most significant positive impact on carbon emissions from the overall perspective, while population urbanization has the most substantial negative effect. The total emissions of the Beijing–Tianjin–Hebei urban cluster far exceeding those of the other four clusters. The factor with the least impact on carbon emissions in the Beijing–Tianjin–Hebei city cluster, the Central Plains city cluster, and the Guanzhong Plain city cluster is energy urbanization. The impact of technological urbanization factors can be positive or negative, the role of spatial urbanization factors is not significant. The northern city clusters should start with transforming energy structure, promote industrial upgrading through innovation, encourage green production and consumption, increase the use of efficient scientific and technological products and services, and promote the development of new urbanization. [ABSTRACT FROM AUTHOR]

Urbanization is a complex phenomenon that has a profound impact on natural resources, economies, climate dynamics, and community structures. This study sets out to analyze the effects of urban sprawl on key urban regions in Bangladesh, covering urban, suburban, and rural landscapes. We used Landsat images from 1992 to 2022, processed and classified using the Google Earth Engine and Random Forest algorithm. Spatial metrics, Tupu method, ANOVA, and spatial regression models helped us quantify and explain land cover changes, their drivers, and consequences. Our findings show that the total built-up area in the five districts expanded from 1,200 km2 in 1992 to 2,800 km2 in 2022, with an overall yearly expansion rate of 3.5%. Meanwhile, vegetation cover declined from 2,500 km2 in 1992 to 1,500 km2 in 2022, with an average yearly loss rate of 2.5%. We identified population growth, economic development, and infrastructure expansion as the main drivers of urbanization, while land degradation, air and water pollution, and loss of biodiversity were the main consequences. Urbanization also had a significant impact on environmental functions, including carbon sequestration, water flow control, and urban heat mitigation, with varying effects across different urban areas and land use types. For instance, we found that carbon storage capacity decreased by 20% in urban areas, while it increased by 10% in rural areas. Our research highlights the crucial role of preserving and enhancing green spaces, including vegetation cover and water bodies, to mitigate urban heat and promote urban resilience. The findings underscore the need for sustainable urbanization, balancing economic growth with environmental protection and climate resilience, using geospatial and remote sensing techniques. [ABSTRACT FROM AUTHOR]

Travelers often change their behavior in reaction to adverse weather conditions. This paper seeks to conduct an empirical evaluation of both ordered and unordered discrete outcome frameworks for examining the adaptive behavior decisions of intercity travelers and investigate the varying effects of explanatory factors on different alternatives of adaptive behavior during adverse weather. The data from 754 respondents in the Beijing-Tianjin-Hebei urban agglomeration, China are collected by a two-phase survey instrument. To capture the unobserved heterogeneity more effectively, this paper develops three advanced models to investigate the variations in intercity travel behavior during adverse weather. Four alternative adaptive behaviors are determined as outcome variables: maintaining original travel plans, changing only the intercity mode, changing the departure date, and canceling the trip, while potential influencing factors including adverse weather conditions, trip-related characteristics, individual attributes and urban agglomeration attributes are statistically assessed. The results indicate that the unordered models consistently outperform their ordered counterparts, and the incorporation of multilayer heterogeneity enhances the model fit. Furthermore, significant factors and their coefficient values vary across the different adaptive behavior alternatives. Intercity travelers demonstrate a higher probability of changing departure dates or canceling trips during snowy and windy days compared to rainy and foggy days. Trains exhibit higher flexibility and reliability during adverse weather, and access attributes significantly affect intercity travel adaptive behavior. Additionally, the analysis of individual and urban agglomeration attributes uncovers variations in adaptive behavior among individuals and cities. These findings provide profound insights into the complexities and variations of intercity travel behavior during adverse weather, and propose practical strategies to mitigate the detrimental impacts of adverse weather on intercity travelers. • Adaptive behavior of intercity travelers during adverse weather is investigated. • Unordered framework outperforms ordered counterparts in adaptive behavior study. • Multilayer unobserved heterogeneity in the adaptive behavior is accounted for. • The varying effects of explanatory factors on different adaptive alternatives are examined. • Practical strategies are proposed to mitigate negative impacts of adverse weather. [ABSTRACT FROM AUTHOR]

The study of the land use optimization of urban agglomerations is of great significance to the rational utilization of land resources and the sustainable development of urban agglomerations. Previous studies have simply regarded the urban agglomeration as a whole area or each city as an isolated individual, without considering the regional coordinated development of urban agglomerations in land use optimization objectives. This study proposed the first attempt to couple Zipf's law and a multiobjective optimization model of land use in an urban agglomeration. Zipf's law was applied to quantify the coordinated development of urban agglomeration and use it as one of the objectives of land use optimization. The genetic algorithm was adopted to establish the optimization model, and different future development scenarios were designed for comparison. The Beijing–Tianjin–Hebei (BTH) urban agglomeration was selected as the study area, and the proposed model obtained effective results within an acceptable time. The Zipf's law–based optimization objective provided a more coordinated scale structure for urban growth and led the urban structure to develop toward the optimized state. There was a conflict, however, between the coordination and the other two objectives (compactness and suitability). Different stakeholders need to consider the trade-offs among these optimization objectives in urban planning. Finally, based on the optimization patterns of local areas, we suggest the following: Some large-scale cities (e.g., Beijing and Tianjin) should strictly control their new urban expansion or transfer part of their resources and population; Langfang and Xingtai should accelerate their development or take over part of the noncapital function of Beijing; and Zhangjiakou and Chengde should optimize their urban morphology and suitability. [ABSTRACT FROM AUTHOR]

As a representative of potential "hidden champions", a concept originating in Germany, specialized and innovative Little Giant Enterprises (LGEs) have become exemplary models for small and medium-sized enterprises (SMEs) in China. These enterprises are regarded as crucial support for realizing the strategy of building a strong manufacturing country and addressing the weaknesses in key industrial areas. This paper begins by examining urban agglomerations, which serve as the main spatial carriers for industrial restructuring and high-quality development in manufacturing. Based on data from LGEs in the Yangtze River Delta (YRD) and Pearl River Delta (PRD) urban agglomerations from 2019 to 2023, the study employs the Random Forest (RF) and Multi-scale Geographically Weighted Regression (MGWR) methods to conduct a comparative analysis of their spatial patterns and influencing factors. The results are as follows: (1) LGEs exhibit spatial clustering in both the YRD and PRD regions. Enterprises in the YRD form a "one-axis-three-core" pattern within a distance of 65 km, while enterprises in the PRD present a "single-axis" pattern within a distance of 30 km, with overall high clustering intensity. (2) The YRD is dominated by traditional manufacturing and supplemented by high-tech services. In contrast, the PRD has a balanced development of high-tech manufacturing and services. Enterprises in different industries are generally characterized by a "multi-point clustering" characteristic, of which the YRD displays a multi-patch distribution and the PRD a point–pole distribution. (3) Factors such as industrial structure, industrial platforms, and logistics levels significantly affect enterprise clustering and exhibit scale effects differences between the two urban clusters. Factors such as industrial platforms, logistics levels, and dependence on foreign trade show positive impacts, while government fiscal expenditure shows a negative impact. Natural geographical location factors exhibit opposite effects in the two regions but are not the primary determinants of enterprise distribution. Each region should leverage its own strengths, improve urban coordination and communication mechanisms within the urban cluster, strengthen the coordination and linkage of the manufacturing industry chain upstream and downstream, and promote high-tech industries, thereby enhancing economic resilience and regional competitiveness. [ABSTRACT FROM AUTHOR]

With the acceleration of urbanization, there has been rapid expansion in urban areas, the associated intense human activity exerting serious impacts on urban environments. Clarifying the interaction between urbanization and the urban environment is important for promoting high-quality sustainable regional development. In this work, a decoupling model is introduced that was used to measure the interaction between (demographic, economic, spatial, and social) urbanization and the urban environment (environmental status, pressure, and response) in the Shanghai–Hangzhou Bay urban agglomeration (SHBUA) from 2003 to 2018. The results showed that: (1) the development level of the four urbanization subsystems improved to different degrees, but overall, the speed of the economic and spatial urbanization (builtup land sprawl) was faster than the social and demographic urbanization; (2) from 2015 to 2018, the relationship between urbanization and the environment in Huzhou, Jiaxing, Ningbo, and Shaoxing was strongly decoupling, indicating negative growth in the urban environment and a trend of environmental deterioration, with increased urbanization coming at the cost of environmental damage; and (3) except for Shanghai, the growth rate of the four subsystems of urbanization in the cities was higher than that of the overall environmental level. Cities with higher urbanization levels were found to be more likely to achieve harmony between urbanization and the urban environment. This study provides a basis for analyzing the relationship between urbanization and the urban environment in urban agglomerations, along with decision-making support for a more harmonious integration of man with nature in the SHBUA. China is currently undergoing a dramatic urbanization process, with populations exploding and construction land expanding in the cities. In addition, ecological cities have been proposed that would increase the area of urban ecological space, causing a negative impact on the urban environment. Despite this process taking place in China, it is unclear how urbanization affects the urban environment, which is of great significance for avoiding the wrong development mode and for realizing sustainable development. From our analysis, we found that, for cities with low levels of urbanization, such as Huzhou, Jiaxing, Ningbo, and Shaoxing, increasing urbanization accompanied a deterioration in the urban environment. Contrastingly, in the more developed cities, such as Shanghai, greater development of the economic and social environment meant more attention could be paid to the construction of the urban environment. Thus, urban environmental improvement and urbanization complement each other. By exploring the relationship between the degree of urbanization and the urban environment, it is possible to inform urban development and environmental management plans in order to mitigate the negative impact of urbanization and improve the urban environment to achieve sustainable urban development for the coming decades. [ABSTRACT FROM AUTHOR]

Urban agglomeration plays a vital role in fostering high-quality and sustainable development in China, where urbanization rates significantly influence both urban and rural environments, generating different economic and socio-spatial impacts that, in turn, influence carbon emissions in cities. To delve into the influencing mechanisms of carbon emissions, this paper examines the spatio-temporal pattern of carbon emissions across 41 cities in the Yangtze River Delta urban agglomeration in China. It utilizes data on economic, social, and spatial factors from 2012 to 2019 and employs a spatial econometric regression model for analysis. The results indicate that carbon emissions of cities in the urban agglomeration exhibited strong spatial correlation from 2012 to 2019, characterized by relatively stable cold and hot spots, along with continuous outward spread of high-value zones. Economic and social factors demonstrate a significant positive spatial correlation with carbon emissions of a city, with weak spatial spillover effects. Spatial factors exhibit correlations with carbon emissions in both the city and neighboring cities, with strong spatial spillover effects. Moreover, the spatial layout and functional division of cities in the urban agglomeration also significantly impact the spatio-temporal pattern of carbon emissions. [ABSTRACT FROM AUTHOR]

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The assessment of ecological space quality (ESQ) and its spatio-temporal change monitoring are crucial for regional ecological management and sustainable development. However, there are few studies on how to construct a comprehensive ESQ assessment system to reveal the spatial and temporal change patterns of ESQ over a long time series. Therefore, this study constructs an ESQ evaluation model with comprehensive ecological characteristics to quantitatively assess the spatio-temporal dynamics of ESQ from 2001 to 2020 based on policy objectives and public demands, using the urban agglomeration in the middle reaches of the Yangtze River as an example. The results show that, in the past 20 years, the mean value of ESQ in urban agglomeration has decreased (−0.179·year−1), and the overall ESQ is dominated by a good level. The ESQ has shifted from improvement (2001–2010) to deterioration (2010–2020) and shows the spatial distribution characteristics of "high in the periphery and center, low in the interior". From the trend of change, the degraded area of ESQ is greater than the improved area, and the degraded area of ESQ will increase in the future compared with the trend of 2001–2020. The distribution of ESQ has a significant spatial agglomeration and scale effect. The hot spots of ESQ at the town scale are mainly concentrated in the central part of urban agglomeration and mountainous areas in the periphery. The cold spots are mainly concentrated in the surrounding areas of central cities (Wuhan, Changsha, and Nanchang). The proposed assessment framework can be used to quantify spatial and temporal changes in ESQ and identify potential ecological space management issues, providing basic information for implementing ecological space protection, restoration, and developing adaptive ESQ management measures. The research results are of significant importance for ecosystem restoration and long-term development in the Yangtze River Basin. [ABSTRACT FROM AUTHOR]

the article reviews and substantiates research methods and data sources on the dynamics of the spatial structure of the largest urban agglomerations in Russia. The object of the study is modern methods for studying urban agglomerations based on new data sources. A case study of the number two urban agglomeration in Russia—St. Petersburg urban agglomeration—shows that interdisciplinary synthesis of socioeconomic geography, regional economics, urban studies, geoinformatics and cartography, land management, and variety of data sources (mobile network operators' data, tax statistics, housing construction, satellite observations, retail chain activity, and road networks), as well as modern GIS equipment, make it possible to evaluate this structure, its changes, and fluctuations. The main objective of the study is to critically rethink the methods of studying the spatial structure of one of the largest urban agglomerations in Russia that developed in the turbulent period between 2014 and 2022. Using a deductive approach, the authors inventoried the available methods for studying urban agglomerations and traditional data sources and obtained updated methods and new sources. Next, the advantages and disadvantages of each group of methods are identified. Using bibliographic analysis, the authors identified the limitations and possibilities for empirical content (availability of specific data sources). Based on their own critical analysis, the authors offer a final expert assessment of the applicability and usefulness of the methods specifically for the St. Petersburg urban agglomeration. The authors' contribution lies in the adaptation of modern groups of methods for studying the spatial structure of cities to study the considered urban agglomeration, taking into account the local specifics. It is expected that development of a modern methodology for studying the spatial structure of the St. Petersburg urban agglomeration, based on a symbiosis of modern methods and data sources, will contribute to studying Russia's largest urban agglomerations. [ABSTRACT FROM AUTHOR]

Study region: The urban agglomeration in the middle reaches of the Yangtze River (MRUA) consisting of 31 cities is a pillar of the Yangtze River Economic Belt and the largest urban agglomeration in China, densely populated, and rapidly urbanizing. Study focus: Extreme precipitation events are affected by rapidly urbanized regions with uneven levels of urbanization. Hence, it is important to explore the spatiotemporal evolution of extreme precipitation in urban agglomerations and the influence of the spatially uneven development of urban areas under rapid large-scale urbanization. New hydrological insights for the region: Extreme precipitation indices (Pmax1d, R20, and PF95) exhibited significant positive trends during 1979–2018 in the MRUA, increasing by 0.43 mm/year, 0.11 day/year, and 2.46 mm/year, respectively. Regression models based on raster urbanization data were constructed, and the impervious area ratio (IA) and landscape shape index (SI) were shown to be the dominant urbanization factors affecting regional extreme precipitation, with a particularly positive spatial correlation with PF95 and Pmax1d at all stages of urbanization. Moreover, the urban-rural comparison results revealed that the difference in SI of each city was positively correlated with the urban heat island intensity. In the three provincial capitals, Pmax1d and R50 were greater in urban centres than in rural areas. This study contributes to a comprehensive understanding in the variability of extreme precipitation events under the influence of large-scale urbanization.

Green development is one of the core elements of high-quality regional development. The Yangtze River Economic Belt stands as the primary area for China’s pursuit of sustainable development. This study analyzes the changes in water resource depletion values within the urban agglomeration of the Yangtze River Economic Belt, as well as the overall scale structure. A total of 44 indicators were selected from the three dimensions, namely green environment, green lifestyle, and green economy, to establish an evaluation index system aimed at assessing the level of green development. Through the application of the entropy-TOPSIS method, geographical detectors, and spatial autocorrelation analysis, the spatial and temporal differentiation variances in green development levels were examined, as well as the influencing factors across 73 cities situated within the three major city clusters from 2000 to 2020. The results show that: (1) The total value of water resource depletion in the three major urban agglomerations exhibits a fluctuating downward trajectory, reaching its lowest point in 2020. (2) City sizes within these three major urban agglomerations are relatively centralized, with high-ranking cities exhibiting limited prominence, showing weak leading advantages. (3) The green development level exhibits an overall upward trend from 2000 to 2020. Cities with higher levels of green development are mainly concentrated in the Yangtze River Delta and the capital cities are situated in the upper and middle reaches. (4) Key influencing factors of the green development level include carbon emissions per unit of GDP, length of drainage pipe per capita, gross domestic product per capita, disposable income of urban residents per capita, and water consumption per unit of GDP. The spatial variance in these indicators explains over 60% of the green development level. Based on the research results, this paper puts forward three policy recommendations: first, to grow the green industry. The second is to promote green municipal infrastructure planning. The third is to encourage regional synergistic cooperation and play the role of radiation leadership of core cities.

China is currently entering a stage of high-quality development, with urban development and governance facing systematic reconstruction of internal and external conditions, showing clear differences and the complex superposition of multi-stage development. The steady progress of urbanization has facilitated significant changes in the population structure of Chinese cities. It is expected that the population and industries will further converge to urban agglomerations and big cities, indicating basic multicenter and network patterns. Therefore, analyzing the negative population growth risks of urban agglomerations at different development stages is crucial. This study examined the cities of 19 urban agglomerations in China by adopting the data of the seventh population census, employing the optimized fuzzy logic method, building a complex network of population flow with ArcGIS and MATLAB platforms, and using the intensity of population flow and the registered population fertility rate to represent exogenous and endogenous growth, respectively. The negative population growth evaluation index system was constructed with five indicators: child ratio, aging rate, average family size, population density, and sex ratio. The risk index of negative population growth was measured using the fuzzy logic method, and the growth mechanism of negative population growth risk in urban agglomerations in China was analyzed using the spatial measurement method. (1) The negative population growth risk of growing urban agglomerations was influenced by both exogenous and endogenous growth, with exogenous growth having a greater impact. (2) The dynamic mechanism of negative population growth risk in large urban agglomerations is exogenous growth, whereas that of nurturing urban agglomerations is endogenous growth. (3) According to the risk of negative population growth in China's urban agglomerations and its influencing factors, negative population growth in 19 urban agglomerations can be divided into eight types. 1) The state of population growth of expanding urban agglomerations can be divided into two types, with the middle reaches of the Yangtze River and Chengdu-Chongqing urban agglomerations as one type; the capital city has a low risk of negative population growth, while other cities have a high risk of negative population growth. The Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei city clusters are the same, with the capital and other cities having a relatively low risk of negative population growth. 2) The status of large urban agglomerations can be divided into two types: Shandong Peninsula, Central Plains, Guanzhong Plain, and Beibu Gulf urban agglomerations. The capital city has a low risk of negative population growth, whereas other cities have a high risk of negative population growth. The risk of negative population growth in capital cities and other cities is relatively low. 3) The state of population growth of cultivated urban agglomerations can be divided into four types: the Harbin and Changsha urban agglomerations and the central and southern Liaoning urban agglomerations, which have a high risk of negative population growth. Meanwhile, the northern slope of the Tianshan Mountain City cluster and the Hubao Eyu City cluster have low risk of negative population growth. The risk of negative population growth is low in the provincial capital city and high in the other cities, while endogenous growth is positive in the provincial capital city and negative in the other cities. In the Jinzhong City, Central Guizhou City, and Central Yunnan City groups, the risk of negative population growth is low in provincial cities and high in other cities. Endogenous growth shows that the capital city and other cities have positive growth. In conclusion, this study posits that upgrading urban agglomerations should consider the spatial balance of population distribution, large urban agglomerations should fulfill their role in "blocking the flow" of big cities, and nurturing urban agglomerations should "consolidate human capital." This study presents a comprehensive and in-depth analysis of the negative population growth risk and its impact mechanisms in different development stages of urban agglomerations. This can provide a decision-making reference for the formulation of scientific and reasonable population and economic policies in various urban agglomerations and plays a significant role for maintaining a long-term stable population, economy, and social growth in the region.

One of Russia's strategic objectives is to identify and create conditions to ensure accelerated development of promising centers of economic growth in the country's regions. In practice, most of these centers are cities of different levels of hierarchy, which create or have the potential to create urban agglomerations on their basis. At the same time, at present, most attention is paid to the study of the largest and large urban agglomerations not only in domestic, but also in the world science; while the real prerequisites and processes of second-tier agglomerations development are studied rather poorly. In this regard, the purpose of this paper was to analyze and identify the specifics of agglomeration processes in several Russian second-tier agglomerations. To achieve this purpose, we used a wide range of both general scientific (analysis, synthesis, structural-functional, etc.) and applied economic and mathematical methods (index method, correlation analysis, calculation of the Theil index). The main conclusions of the research was that the key trend of these agglomerations' development was the increasing concentration of an already high share of regional production, investment, and population against the background of growing intra-regional heterogeneity. At the same time, agglomeration processes themselves spread only to the territory closest to the core, which is manifested in the convergence of growth rates of these territories in terms of key socio-economic indicators. All this proves the underdevelopment of the satellite zone of second-tier agglomerations and the hypertrophied development of the core: weak interconnectedness of their reproductive processes, which may be a threat to the development of such agglomerations as integrated socio-economic systems and growth centers of regional and macro-regional significance in the future. The authors showed that a number of northern/arctic agglomerations (Surgut, Arkhangelsk) have a significant development potential due to not only the formed economic base of their satellite zone, but also socio-economic connectivity along the line "core-satellite zone". The scientific novelty of the presented research lies in the development of approaches, substantiation of methodological tools for assessing agglomeration processes, and identification of the specifics of these processes in Russian second-tier agglomerations on the basis of its testing.

Abstract This paper examines the coupling coordination degree between digital economy and green technology innovation in 19 urban agglomerations across China from 2011 to 2020. Through the analysis of the coupling coordination degree model, spatial autocorrelation, multi-distance spatial clustering analysis, kernel density analysis and grey correlation model, this study uncovers the mechanism of coupling between digital economy and green technology in Chinese urban agglomerations. Data analysis revealed a significant increase in the coupling coordination between the digital economy and green technology innovation within urban agglomerations. However, there are noticeable spatial imbalances in this trend. Additionally, the multi-distance spatial distance analysis highlights a shift from a random distribution to a clustered distribution of spatial characteristics. The polarization features vary among each urban agglomeration and exhibit a significant positive spatial correlation. Factors such as economic sustainability, creative talent, policy support, digital impetus, and technological support will affect the coupling mechanism of green technology innovation and the digital economy in China's urban agglomerations. Policy recommendations are proposed to foster the development of the digital economy, promote coordinated growth within and beyond urban clusters, and ultimately build a digital ecological civilization that is both green and intelligent.

ABSTRACTChina’s massive urbanisation development will undoubtedly serve as a global reference. Due to the uncertainty of statistical data, nighttime light (NTL) data have emerged as alternative data for urbanisation evaluation. Here, the application of the Prolonged Artificial NTL Dataset of China (1984–2020) has been newly expanded. Total-value statistical, complex NTL index (CNLI), NTL concentration degree, rank-size rule, and Markov transfer matrix were used to systematically mine information about urban change from multiple perspectives. China’s urbanisation exhibited rapid growth and outwards expansion. The total percentage increase in NTL brightness and NTL area was 409.38% and 302.58%, respectively. The Yangtze River Delta urban agglomeration of East China had the fastest urbanisation (CNLI Trend = 0.0057/a, p 95%) in city size type transition. The spatiotemporal changes in NTL obtained were of great significance for monitoring urban expansion patterns, making government decisions, and quantifying China’s sustainable development.

Land use efficiency is an indicator that measures the level of regional land resource allocation and optimization. The influence of policies tends to lead to the restructuring of regional land use and allocation in urban agglomerations, and the degree of optimization in land use efficiency has become a critical component in evaluating policy performance. In light of this, it is particularly necessary to clarify the theoretical relationship between the establishment of urban agglomerations and land use efficiency and to understand their underlying mechanisms. Additionally, it is particularly important to summarize the spatial differentiation of their effects. This study constructed a theoretical analysis framework to investigate the impact of urban agglomeration establishment on land use efficiency, deriving from the policy pathways of establishing urban agglomerations. It also explored the mediating roles of public service supply, industrial agglomeration, and technological innovation, as well as the moderating effects of geographical, institutional, and economic disparities. Building upon this foundation, the approval and implementation of national-level urban agglomeration planning were treated as a quasinatural experiment for further investigation. Based on the panel data of 244 prefecture-level and above cities in China from 2009 to 2020, this study used a staggered difference-in-differences model to empirically test the impact of establishing urban agglomerations on land use efficiency. In addition, the mediating effects were tested based on three types of pathways, and heterogeneity effects were examined using a 'center-periphery' approach with multiple types of spatial distances to analyze the mechanisms of influence. The study findings were as follows: (1) The establishment of urban agglomerations had a significant and positive impact on land use efficiency, and this effect continued and was strengthened after the establishment of national-level urban agglomerations. (2) The impact of establishing national-level urban agglomerations on land use efficiency was mediated by three factors: public service provision, industrial agglomeration, and technological innovation. However, after adjusting for policy timing, only the mediating effects of industrial agglomeration and technological innovation remained, and their effects were consistent with the establishment of national-level urban agglomerations. (3) The promotion of land use efficiency by national-level urban agglomerations exhibited spatial heterogeneity, with the effect being slightly suppressed as geographic and institutional distances increased. After adjusting for policy timing, this promoting effect was shown to exhibit spatial heterogeneity, being slightly suppressed only with increasing economic distances. Based on these findings, policy recommendations are made to further strengthen regional public investment through the allocation of resources in urban clusters, align industrial agglomeration and technological innovation with rational industry layout and division of labor, and enhance regional institutional reforms and integration to achieve regional balance. [ABSTRACT FROM AUTHOR]

Clarifying the relationship between urbanization and farmland abandonment in urban agglomerations (UAs) is crucial to guide the formulation of arable land management policies and strategies for sustainable urban development. Despite numerous studies confirming the correlation between farmland abandonment and certain urbanization factors, the exploration of the patterns and underlying mechanisms of farmland abandonment in China's UAs remains worthy of systematic investigation. In this study, we conducted an analysis of the spatiotemporal trends in farmland abandonment and examined the key drivers of farmland abandonment in four representative Chinese UAs—Beijing–Tianjin–Hebei (BTH), Chengdu–Chongqing (CC), Pearl River Delta (PRD), and Yangtze River Delta (YRD). Our findings reveal that farmland abandonment has been intensified with increasing fragmentation and aggregation patches across these UAs. Abandonment experience was the main driver of continuous abandonment. Moreover, natural conditions persistently influenced farmland abandonment in the BTH, while land urbanization and economic urbanization were predominant drivers in the CC. The abandonment in the PRD was mainly driven by population urbanization, while the abandonment in the YRD was primarily driven by economic urbanization and land urbanization. The research findings provide data support and scientific explanation for land policy-making in these typical UAs under different development strategies. [ABSTRACT FROM AUTHOR]

China has fully become an aging society, and the scientific response to population aging has become a major task that the country must face in the future. Research on population aging in the Chengdu-Chongqing urban agglomeration (CCUA) can provide a scientific basis for future population management in the CCUA. This paper applies spatial autocorrelation, geodetection, and other methods to analyze the temporal and spatial pattern of population aging and its driving factors in the CCUA from 2000 to 2020, taking districts (counties) as the basic unit and combining them with the spatial structure of the urban agglomeration. The results show that: ① in the time dimension, the population aging in CCUA has gone through the evolution process of "mild–moderate–heavy"; in the spatial dimension, the influence of the urban agglomeration's development planning axes on the spatial differentiation of the aging population has become more and more prominent. ② The aging level has a strong spatial correlation, and with time, the spatial correlation has changed from weak to strong, and the spatial difference has increased. The dual core city shows a typical spatial pattern of a decreasing aging level in the core area and an increasing aging level in the peripheral area, and the heavily aging area is spreading along the axis. ③ The overall aging speed is high, and the aging speeds of the core cities and node cities are lower than those of other regions. There is a clearer positive correlation between the aging level and the speed of aging, showing the characteristic of "the older the faster". ④ Endogenous factors such as the aging level and fertility level at the beginning of the period have a significant determining power on the change in the aging level, while exogenous factors such as the in-migration rate and the out-migration rate have a persistent determining power on the urban agglomerations and key areas (core cities, central cities, main axes of development, city belts, and dense urban areas). [ABSTRACT FROM AUTHOR]

Recently, researchers have become increasingly interested in urban resilience, which can be used to comprehensively evaluate the quality of urban development. Although some studies have addressed the effects of China's national urban agglomeration (NUA) policy on the economic and environmental resilience of Chinese cities, scholars have not yet adequately addressed the impact of NUA on comprehensive urban resilience. Accordingly, this study introduced a theoretical framework to explore the effects of NUA on comprehensive urban resilience in China. Specifically, this study conducted a quasi-natural experiment with NUA and adopted a difference-in-differences (DID) method to evaluate its effect on China's comprehensive urban resilience. As no widely acknowledged urban resilience evaluation method yet exists, we employed an entropy-weighted "technique for order preference by similarity to an ideal solution" (TOPSIS) to assign comprehensive urban resilience values to Chinese cities at the prefecture level or above based on the multiple economic resilience index, the social resilience index, the environmental resilience index, and the technological resilience index. The results indicate that NUA not only directly improves comprehensive urban resilience but also enhances it through the mediating effects of trade openness and industrial structure upgrading. In addition, the study revealed that city heterogeneity can impact NUA's effect on comprehensive urban resilience. These results not only expand current theoretical understanding of the effects of urban agglomeration on urban resilience but also offer insights useful for improving comprehensive urban resilience to facilitate the high-quality and sustainable development of cities. [ABSTRACT FROM AUTHOR]

To investigate the spatial and temporal distribution, sources, and ecological risk of soil polycyclic aromatic hydrocarbons (PAHs) in China's urban agglomerations from 2000 to 2020, a comprehensive search strategy was employed using the keywords "soil", "PAHs", and "city". A total of 122 relevant studies that provided information on individual PAH content during the specified time period were collected. These studies encompassed 20 urban agglomerations in China, which were further categorized into two distinct periods: 2000 to 2010 and 2011 to 2020. The diagnostic ratio method and principal component analysis were employed to identify the sources of PAHs, and a risk quotient model was used to evaluate the soil ecological risk. The results revealed the average PAH content in the 20 urban agglomerations in China from 2011 to 2020 was 2,439 ± 4,633 ng·g-1, which exceeded the severe pollution level cut-off (> 1,000 ng·g-1). The soil PAH content in the period from 2011 to 2020 decreased by 28% compared to the soil PAH content in the period from 2000 to 2010. Soil PAH pollution was more severe in the northern urban agglomerations than in the southern urban agglomerations. Diagnostic ratios and principal component analysis demonstrated that the principal sources in most urban agglomerations in China were traffic and coal combustion. GeoDetector found that coal and fuel oil consumption were the main factors affecting the spatial differentiation of PAHs. The ecological risk quotient showed that approximately 80% of the urban agglomerations were at a medium-high ecological risk from 2000 to 2010, compared with 72% from 2011 to 2020. Thus, it is necessary to deepen energy structure reform to alleviate the threat of serious pollution caused by coal and fuel oil in urban agglomerations. [ABSTRACT FROM AUTHOR]

China is currently entering a stage of high-quality development, with urban development and governance facing systematic reconstruction of internal and external conditions, showing clear differences and the complex superposition of multi-stage development. The steady progress of urbanization has facilitated significant changes in the population structure of Chinese cities. It is expected that the population and industries will further converge to urban agglomerations and big cities, indicating basic multicenter and network patterns. Therefore, analyzing the negative population growth risks of urban agglomerations at different development stages is crucial. This study examined the cities of 19 urban agglomerations in China by adopting the data of the seventh population census, employing the optimized fuzzy logic method, building a complex network of population flow with ArcGIS and MATLAB platforms, and using the intensity of population flow and the registered population fertility rate to represent exogenous and endogenous growth, respectively. The negative population growth evaluation index system was constructed with five indicators: child ratio, aging rate, average family size, population density, and sex ratio. The risk index of negative population growth was measured using the fuzzy logic method, and the growth mechanism of negative population growth risk in urban agglomerations in China was analyzed using the spatial measurement method. (1) The negative population growth risk of growing urban agglomerations was influenced by both exogenous and endogenous growth, with exogenous growth having a greater impact. (2) The dynamic mechanism of negative population growth risk in large urban agglomerations is exogenous growth, whereas that of nurturing urban agglomerations is endogenous growth. (3) According to the risk of negative population growth in China's urban agglomerations and its influencing factors, negative population growth in 19 urban agglomerations can be divided into eight types. 1) The state of population growth of expanding urban agglomerations can be divided into two types, with the middle reaches of the Yangtze River and Chengdu-Chongqing urban agglomerations as one type; the capital city has a low risk of negative population growth, while other cities have a high risk of negative population growth. The Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei city clusters are the same, with the capital and other cities having a relatively low risk of negative population growth. 2) The status of large urban agglomerations can be divided into two types: Shandong Peninsula, Central Plains, Guanzhong Plain, and Beibu Gulf urban agglomerations. The capital city has a low risk of negative population growth, whereas other cities have a high risk of negative population growth. The risk of negative population growth in capital cities and other cities is relatively low. 3) The state of population growth of cultivated urban agglomerations can be divided into four types: the Harbin and Changsha urban agglomerations and the central and southern Liaoning urban agglomerations, which have a high risk of negative population growth. Meanwhile, the northern slope of the Tianshan Mountain City cluster and the Hubao Eyu City cluster have low risk of negative population growth. The risk of negative population growth is low in the provincial capital city and high in the other cities, while endogenous growth is positive in the provincial capital city and negative in the other cities. In the Jinzhong City, Central Guizhou City, and Central Yunnan City groups, the risk of negative population growth is low in provincial cities and high in other cities. Endogenous growth shows that the capital city and other cities have positive growth. In conclusion, this study posits that upgrading urban agglomerations should consider the spatial balance of population distribution, large urban agglomerations should fulfill their role in "blocking the flow" of big cities, and nurturing urban agglomerations should "consolidate human capital." This study presents a comprehensive and in-depth analysis of the negative population growth risk and its impact mechanisms in different development stages of urban agglomerations. This can provide a decision-making reference for the formulation of scientific and reasonable population and economic policies in various urban agglomerations and plays a significant role for maintaining a long-term stable population, economy, and social growth in the region. [ABSTRACT FROM AUTHOR]