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In order to explore the causal relationship between the level of urban digital construction and urban economic growth, this paper takes 280 cities in China as the research object and constructs a comprehensive indicator evaluation system covering digital infrastructure, overall economic level, innovation development level, digital industry development status, and ecological environment conditions. Using the entropy method to weigh various indicators, this paper has obtained the evaluation results of the digital construction level of each city from 2011 to 2021. Furthermore, a panel data regression model is used to empirically analyze the impact of urban digital construction level on urban economic growth. The results show that for every 1% increase in the level of urban digital construction, the GDP will increase by 0.974. Through the above research, we hope to further enrich the theoretical and empirical research in the field of the digital economy, provide a scientific and reasonable method for quantitatively evaluating the level of urban digital construction, and provide decision-making references for improving the level of urban digital construction and promoting sustainable urban development. [ABSTRACT FROM AUTHOR]

The coexistence of urban expansion and shrinkage in China has become increasingly apparent; therefore, the current strategic model of growth-oriented urban planning as the top-level design needs to be adjusted. This paper focuses on the city of Baishan, which is a typical shrinking city in China, and explores the feasibility of implementing the concept of smart shrinkage planning in shrinking cities in China by constructing a coupled PLUS-SD model. The results demonstrate the following conclusions: (1) The overall simulation of the coupled PLUS-SD model is superior to that of the PLUS model. In Baishan, the areas with the most changes in construction land will be located at the edges of the landforms by 2030. (2) Using the traditional planning scenario would only exacerbate the rate of construction land expansion in Baishan, deepening the incongruity between the city's population and construction land. (3) The smart shrinkage scenario will require strict control of the scale of construction land and optimization of the structure of the urban construction land, which would push the city in the direction of healthy and sustainable development. (4) The concept of smart shrinkage planning is a scientific and feasible plan for realizing the efficient and sustainable use of construction land in shrinking cities. [ABSTRACT FROM AUTHOR]

The recent economic advances made by China have now obliged the country to address the need for sustainable urban redevelopment. Unlike other recently developed areas in China, urban villages are in dire need of improvement. Consequently, the redevelopment of urban villages has garnered considerable public and academic interest. However, a comprehensive understanding is lacking on the drivers of urban village redevelopment in China. This study aims to fill this gap through a comprehensive survey of existing literature on redevelopment of urban villages. A total of 167 papers have been retrieved from the Web of Science Core Collection database. A bibliometric analysis and a critical content analysis are conducted on the bases of these papers. We found at least three main processes which have driven urban village redevelopment in China. First, the growth of urban population and their income level has created a strong emerging demand to improve urban living conditions, which has triggered the restructuring of urban villages with sub-standard built environment into high-quality urban spaces. Second, from the production side, the market-oriented land reforms and the developers' pursuit of land-related investment returns from land rent gap is also a strong driving force for demolition and redevelopment of urban villages. Lastly, the states and local governments have played a critical role in promoting urban village redevelopment and integrating informal urban spaces into formal urban areas. This research concludes with an evaluation of current studies on urban village redevelopment and provides suggestions for further research in the future. [ABSTRACT FROM AUTHOR]

Urban logistics is important to a city's sustainable growth and development. With the increase in population and the economic growth in urban areas, the issue of congestion and the negative influence of transport of goods on people and the environment is one of the most important factors in the development of urban logistics. By determining the optimal location of urban logistics centres, total transport costs of logistics, the flow of goods in urban areas and the greenhouse gas emissions will be reduced. However, the traditional methods are easily influenced by the ambiguity of objective data, which makes it difficult to accurately describe the logistics demand in the urban area. To address this issue, the improved location–allocation model for urban logistics centres based on truck trajectory data is proposed. After extracting the origin–destination points, the logistics service demand can be estimated by the DBSCAN (density-based spatial clustering of applications with noise) clustering method. Then, the location–allocation of logistics centres is determined by an improved P-median method with the supply capacity limitation for simultaneous delivery of goods in the logistics centres. To validate the model, taking Wuhan, a central logistics city in China, as an example, the model can effectively ensure the equitable distribution of logistics facilities, minimize freight expenses, achieve more uniformity in logistics center services, and foster sustainable development of the city's logistics sector. [ABSTRACT FROM AUTHOR]

The Yangtze River Economic Belt (YREB), an important industrial belt for food security for China, is facing the challenge of decreasing cultivated land in the process of rapid urbanization. In this case, how to improve the cultivated land use efficiency (CLUE) has become the top priority. Based on data from 108 cities of YREB from 2001 to 2019, we measured CLUE using a slack-based measure with undesirable output (SBM-Undesirable). The high-value area of CLUE shows a trend from multi-core agglomeration to two-core agglomeration, mainly concentrated in Chengdu-Chongqing urban agglomeration and the northern part of the YREB. Then the paper examines the spatial effect of urbanization on CLUE using the Spatial Error Model (SEM). The result shows that population urbanization has significantly promoted the improvement of CLUE in YREB during the sample period. With each percentage point increase in population urbanization, CLUE will increase by 2.99%. Land urbanization has a negative impact on CLUE, for each percent increase in the expansion of urban spatial scope, CLUE will decrease by 0.06%. The spatial heterogeneity analysis shows that population urbanization in the lower reaches has significantly promoted CLUE, with a coefficient of 1.053. The population urbanization level in the middle and lower reaches of the region has no obvious effect on CLUE. The coefficient of land urbanization in the downstream region is 0.35, which significantly promotes CLUE. The coefficient in the middle is −0.26, which implies the CLUE decreases by 0.26% for every one percentage point increase in land urbanization. Land urbanization in the upper has no significant impact on the CLUE. Policy implications include improving the quality of the three major urban clusters along the YREB, building an ecologic protective screen in the upper, encouraging a new agricultural management system and detailed regulations related to the cultivated land protection in YREB. [ABSTRACT FROM AUTHOR]

Modern cities require urban compact development to be sustainable. The evaluation of urban compact development may help create more accurate and realistic policies. The spatio-temporal dynamic evolution of urban compact development efficiency and its regional differences in China are examined in this study. This paper analysis uses 282 cities from 2005 to 2021. The unexpected output super-efficiency SBM model measures urban compact development efficiency. In this study, the urban compact development efficiency's spatial and temporal patterns are also examined using kernel density estimation (KDE) and the Theil index (TI). The average efficiency of urban compact development in China has decreased slightly. However, compact efficiency disparities are decreasing. Eastern cities have a relatively stable compact efficiency, while central and western cities vary more. The compact efficiency polarisation has not changed fundamentally. The compact city growth model's spatial agglomeration is poor, limiting its spatial spillover impact. Thus, compact urban development is necessary to speed up planning, facilitate inter-city production factor movement by creating a comprehensive transport network, and maximise co-location benefits with the regional integration strategy. This method will gradually reduce regional urban development disparities and push Chinese cities towards more refined and sustainable compact development. [ABSTRACT FROM AUTHOR]

Green development is a significant concept that cannot be ignored in contemporary society. However, in the context of China's transition from high-speed growth to high-quality development, the complex impact of urban development has brought great challenges to the urban green environment. In this paper, the impact of urban development on green development efficiency (GDE) was studied. First and foremost, a Super-SBM model was introduced to measure the GDE of 41 cities in the Yangtze River Delta during 2009–2018. Moreover, a Tobit model was used to analyze the correlation between four urban development factors, including economic development and GDE. According to the results, the mean GDE of the Yangtze River Delta is 0.824, and the GDE in most cities there has shown a fluctuating growth trend in this decade. By comparison, the GDEs of coastal cities and cities in the southeast of the Yangtze River Delta were generally higher than those of cities in the north, indicating that the green development is geographically unbalanced, and there is spatial heterogeneity in the area studied. The study's results also suggest that the urban economic development, innovation level, and government planning play a significant role in stimulating urban green development, and that the expansion of urban construction area hinders the improvement of GDE. [ABSTRACT FROM AUTHOR]

While rapid urbanization promotes social and economic development, it exacerbates human outdoor thermal comfort, which increases the risks to human health. This paper uses four thermal comfort indices and multiple satellite observations to explore the urbanization effect on summer heat stress in Guangdong from 1979–2018, a coastal province of China. Two types of thermal comfort index are used here, namely the direct thermal comfort index (Heat Index, HI; Temperature–Humidity Index, THI; Discomfort Index, DI) and the physiological thermal comfort index (Universal Thermal Climate Index, UTCI). We compare the differences in the urbanization effects on the changes in the three direct thermal comfort indices (HI, THI, and DI) and a physiological thermal comfort index (UTCI). The results show that all four thermal comfort indices indicate an overall warming trend. Of them, urban sites show a higher warming trend than rural sites, indicating that heat stress changes are significantly influenced by urbanization from 1979–2018, which is consistent with the effect of urbanization on surface air temperature. However, except for the UTCI, this warming of direct thermal comfort indices affected by urbanization has become insignificant under the regional vegetation greening from 2004–2018 (also consistent with surface air temperature). This is primarily attributed to the different effects of wind speed on the physiological thermal comfort index in urban and rural areas: Decreasing wind speeds in urban areas lead to an increase in UTCI, while wind speeds in rural areas increase instead and decrease UTCI, thus widening the UTCI differences between urban and rural areas. Our results indicate that urbanization has a different effect on thermal comfort indices. When using the thermal comfort index, it is necessary to consider that different thermal comfort indices may bring different results. UTCI considers more factors that affect human heat perception, so it can better describe human outdoor thermal comfort. It also highlights the importance of urban ventilation and urban greenness in mitigating urban outdoor thermal comfort in the sustainable construction of future urbanization in coastal cities. [ABSTRACT FROM AUTHOR]

With the rapid development of digital finance, the implementation of digital infrastructure is becoming increasingly significant. Broadband construction is an important part of the communication network, and can promote urban infrastructure in cities. However, whether the development of broadband can affect housing prices by affecting the urban infrastructure and the convenience of residents is a question worth addressing. In this study, using panel data regarding cities in China, we used the spatial multi-period difference-in-differences (SDID) model to investigate the utility of the Broadband China Policy (BCP) on urban house prices and the mechanism of impact. We found that the BCP can increase house prices, and that this impact has a positive spatial spillover effect. This conclusion still held after a series of tests such as parallel trend tests, placebo tests, and the exclusion of other policy effects. The BCP can increase house prices by improving urban infrastructure, promoting urbanization, and optimizing urban industrial structure. In addition, we conducted a heterogeneity analysis by taking into consideration the administrative level, economic development level, and location of cities. The findings of this paper not only enrich the research on the BCP and housing prices, they also provide policy recommendations in terms of urban land use and sustainable development. [ABSTRACT FROM AUTHOR]

Urban form is closely related to CO2 emissions and the accurate estimation of the impact of urban form on CO2 emissions plays an important role in tackling climate change caused by the emission of greenhouse gases. In this paper, we quantitatively investigate the effects of urban form on CO2 emission and its efficiency from three perspectives: urban expansion, compactness, and complexity. By using panel quantile regression with fixed effects, we show that: (1) The estimation results about the relationship between urban form and CO2 emission and its efficiency are consistent with the literature. (2) The partial effects of urban form without controlling for socioeconomic factors are heterogeneous throughout the conditional distribution of CO2 emission and its efficiency. (3) Taking into consideration that the partial effects of urban form on CO2 emission and its efficiency might depend on the magnitude of socioeconomic factors, we include interaction terms into our model and find that the interaction effects between socioeconomic factors and urban form are heterogeneous across cities with different levels of CO2 emission and its efficiency. Our empirical findings shed light on the optimization of urban form in improving the CO2 emission efficiency, providing policy makers with effective ways of reducing CO2 emissions across cities with different levels of CO2 emissions. [ABSTRACT FROM AUTHOR]

Industrial agglomeration is one of the primary driving factors in city creation, and the improvement of urban land green use efficiency (ULGUE) is an important part in green development. This study concentrates on the impact of industrial agglomeration on ULGUE in the process of urbanization. Based on the panel data of 283 cities in China from 2003 to 2019, this paper constructs a super efficiency SBM-DEA model including unexpected outputs to evaluate ULGUE. Using a spatial Durbin model, we examine the spatial spillover effects of manufacturing and productive services agglomeration on ULGUE. The results show the following: (1) There has been fluctuation over the study period, which can be classified into three stages, and ULGUE in China as a whole is on the rise. (2) Chinese ULGUE has increased greatly in the western and northeastern regions, changed massively in the eastern region, and stayed largely steady in the middle region. The degree of manufacturing agglomeration is further improved, exhibiting a feature resembling a ladder, with high concentrations in the southeast coastal region and low concentrations in the interior. Production service industry agglomeration intensity has declined, revealing a more dispersed spatial pattern. (3) The rise in local ULGUE will have a beneficial impact on the ULGUE of spatially correlated regions, according to ULGUE's relatively strong spillover effect. (4) Manufacturing agglomerations can enhance the ULGUE in the neighborhood, but it is not obvious how this will impact the local regions. The agglomeration of production service industry can enhance the improvement of ULGUE in local and spatially correlated regions, but the direct effect is weak. (5) The integration of the manufacturing and productive service industry does not quite strengthen its stimulatory effects on the growth of ULGUE. [ABSTRACT FROM AUTHOR]

With globalization and informatization, cross-border areas have become increasingly critical interactive spaces, experiencing rapid development and extensive changes in residents' cross-border travel, constantly changing the spatial patterns of neighboring cities. However, existing studies lack in-depth discussions of the new spatiotemporal characteristics of human activities, spatial pattern evolution, and the driving factors behind them. Therefore, taking the Guangzhou-Foshan metropolitan area as a case, this paper focus on the analysis of the cross-city travel of residents in these border areas in 2019, and investigated the evolution of spatial patterns and the driving forces in the border area during 1985–2020. We found that, instead of the previous one-way attraction pattern caused by the spread of residence, a large number of cross-city trips for leisure and entertainment purposes emerged, and the one-way unbalanced flow, "Foshan to Guangzhou", changed to two-way circulation. We also explore the scenario in which the travel behavior of urban dwellers in these two cities considerably interacts with the effect of urban structure to produce the observed mobility patterns. Second, we determined the spatial pattern of the Guangzhou-Foshan region from 1985 to 2020 to be on of spreading expansion, with Liwan District as the central core, connecting to several sub-centers. The cross-border area in the Guangzhou-Foshan region represented a compact, extremely high degree of integration and a well-matched functional space. Third, driven by the forces stemming from the planning guidelines and the improving transportation network construction in the border area, the growth points of the two cities continued to expand toward the borderline regarding integrated development, while the growth axis was mainly in the direction of the city border, urban arterial roads, and subway lines. We concluded with development suggestions for increasing travel interactions and optimizing spatial patterns to build a common vision of the whole Guangzhou-Foshan pattern of integration. [ABSTRACT FROM AUTHOR]

Although some methods have identified the physical urban area to a certain extent, the driving factors for the identification threshold have not been studied deeply. In this paper, vector building data and road intersection data are used for comparative validation based on the urban expansion curve method to identify the physical urban area using the meso-city scale. The geographical detector technique is used to detect how and to what extent the urban spatial structure factors, geographical environment factors and social economic factors affect the optimal distance threshold of 22 administrative districts in the Chongqing municipality. The results based on the vector buildings are more precise and show the characteristics of the physical urban area of core-periphery distribution and the distribution along the water corridor. From the results of quantitative attribution, it was found that the road network density, building density, urbanization rate and urban population density, and their interaction with regional GDP, play a critical role in the optimal distance threshold, with the index value of influence degree ≥0.79. Under the influence of different factors, the optimal distance thresholds of 22 administrative districts show adaptive characteristics. Looking forward to the future, this study provides ideas for further research on the morphological characteristics and distribution laws of multi-spatial scale cities. [ABSTRACT FROM AUTHOR]

One of the primary aims of China's territory spatial planning is to control the urban sprawl of local municipals and prevent regional competition and the negative consequences on the environment—which emphasizes the top-down spatial regulation. Indeed, the traditional cellular automaton (CA) model still has limitations when applied to the whole administration area since it may ignore the differences among cities and towns. Thus, this paper proposed a CM-CA (clustering, multi-level logit regression, integrated with cellular automaton) framework to simulate urban growth boundaries for cities and towns simultaneously. The significant novelty of this framework is to integrate several urban growth modes for all cities and towns. We applied our approach to the city of Xi'an, China, and the results showed satisfactory simulation accuracy of a CM-CA model for multiple cities and towns, and the clusters' effects contributed 74% of the land change variance. Our study provides technical support for urban growth boundary delineation in China's spatial planning. [ABSTRACT FROM AUTHOR]

China's rapid urbanization has been accompanied by serious urban sprawl. Instead of measuring the physical urban boundaries (PUBs), most of existing studies in China rely on yearbook statistics to describe the growth of urbanized area; therefore, the understanding of the actual form and quantity of urban sprawl are restrained. As the statistical unit is generally at or above the county level, these studies tend to omit the lower-level "larger towns". This paper discusses the measurement of urban sprawl and compactness using multi-source data on the GIS platform through the case study of the Wen-Tai region in China. GlobeLand30 remote sensing image data, vector road network data, NPP/VIIRS nighttime light data, and points of interest (POIs) data are adopted. The new method enhances the identification of built-up areas in larger towns. Besides, the 2020s' PUBs of this region, data for 2010 and 2000 are retraced to assess the urban expansion rate, and two approaches are used to discuss the urban growth pattern. Additionally, a compactness model is constructed from four dimensions, i.e., the compactness of external contour, accessibility of road network, land-use intensity, and functional diversity, by which a high-resolution visual analysis tool is created for the provincial government to monitor urban sprawl. [ABSTRACT FROM AUTHOR]

Chinese development priorities have, since 2012, been formally framed under the slogan "Ecological Civilization" (EC). Simultaneously, urban agriculture (UA) has emerged as a potential strategy to contribute to urban food security in China, in wake of the COVID-19 pandemic. In this paper, we interrogate EC as an approach to urban and agricultural development in China and explore how EC manifests in practical terms, through a case study of urban agriculture. Over four months, we conducted on-site interviews and surveys with UA practitioners in four Chinese cities to understand how their experiences are negotiated with the state, in the context of EC. We find through our case study that capital-intensive and peri-urban approaches to UA are favoured in the context of EC, while small-scale intra-urban initiatives are actively discouraged in policy but passively accepted in practice and enforcement. This is despite all forms of UA promoting key goals for EC, including beautifying urban areas, increasing the quality of life for urban residents, and reconnecting individuals with food growing culture. Despite novel developments in innovative agricultural practices in both rural and urban contexts, the EC pathway risks overlooking grassroots initiatives and meeting local residents' needs. [ABSTRACT FROM AUTHOR]

As the most concentrated area of human activities, cities consume many natural resources and discharge a large amount of waste into the natural environment, which has a huge environmental impact. Most of the ecological and environmental problems, such as environmental pollution, global climate change, and loss of biodiversity, are related to urban systems. How to coordinate urban development with the urban ecological carrying capacity is related to the destiny of the city itself, and also to whether its surrounding areas can successfully achieve the goal of high environmental quality and sustainable development. At present, the theory and methods of urban ecological carrying capacity research are relatively new, which has caused problems for policy makers in practical applications. This paper proposes a theoretical framework for urban ecological carrying capacity assessment based on the analysis of ecosystem services supply and demand. Combined with multi-source spatial data and spatial model methods, the supply and demand of ecosystem services were spatially quantified. The capital city of China, Beijing, was the case study area for this research. The spatial differentiation of the supply–demand relationship of ecosystem services is formed. The priority areas for ecological carrying capacity improvement at pixel scale and at the administrative level are obtained, respectively. The results show that the first priority area is concentrated in the center of the urban area, accounting for 31.11% of the total area of Beijing. According to the secondary zone and the specific ecosystem service type, the ecological carrying capacity improvement strategy of different zones is proposed. This study provides a new perspective for investigating urban ecological carrying capacity and for identifying the priority areas for ecological carrying capacity improvement, and helps the policy-makers to design tailored policy actions. [ABSTRACT FROM AUTHOR]

Nowadays, cities meet numerous sustainable development challenges in facing growing urban populations and expanding urban areas. The monitoring and simulation of land use and land-cover change have become essential tools for understanding and managing urbanization. This paper interprets and predicts the expansion of seven different land use types in the study area, using the PLUS model, which combines the Land use Expansion Analysis Strategy (LEAS) and the CA model, based on the multi-class random patch seed (CARS) model. By choosing a variety of driving factors, the PLUS model simulates urban expansion in the metropolitan area of Hangzhou. The accuracy of the simulation, manifested as the kappa coefficient of urban land, increased to more than 84%, and the kappa coefficient of other land use types was more than 90%. To a certain extent, the PLUS model used in this study solves the CA model's deficiencies in conversion rule mining strategy and landscape dynamic change simulation strategy. The results show that various types of land use changes obtained using this method have a high degree of accuracy and can be used to simulate urban expansion, especially over short periods. [ABSTRACT FROM AUTHOR]

The State Council of the People's Republic of China issued the National Territory Spatial Planning Outline (2016--2030), which is a fundamental guide and blueprint for China to achieve its Sustainable Development Goals (SDGs). Based on its sustainable-city initiatives, this paper establishes a "four-space (4S)" assessment framework, and measured the urban development quality (UDQ) of 336 cities in China. Then we analyzed the spatial patterns of UDQ, and identified the main obstacles. Our results show that there is considerable room for improvement in UDQ in China. The spatial pattern of UDQ shows that the eastern economic zone score is higher than the western score and the northern lower than the southern. The spatial efficiency, structure, and quality in Chinese cities have significant hierarchical structure, while the form pattern is complicated. The most important obstacle to China's high-quality development is spatial efficiency. The most significant limiting indicator is the industrial structure, followed by land output level and land consumption per unit GDP. Our findings help enhance the effectiveness of National Territory Spatial Planning policy implementation and guide China's urban planning and management to achieve sustainability. [ABSTRACT FROM AUTHOR]

As the largest developing nation, China is currently experiencing rapid urban growth. Conducting a thorough scientific assessment of this expansion and its ecological consequences is of paramount importance for advancing China's ecological civilization and aligning with the United Nations' Sustainable Development Goals. This study employs multi-source remote sensing data to investigate the spatiotemporal trends in Chinese urban development and explore its impact on the ecological environment. From 2013 to 2021, the findings indicate an increasing trend in China's total nocturnal light, with the southern and central regions exhibiting higher growth rates. This suggests a decade-long expansion of Chinese cities, especially in the southern and central regions. However, the impact of urban expansion on ecological quality varies. Beijing, Shenyang, and Xi'an have witnessed improved environmental quality, while Kunming and Shenzhen have experienced minimal changes, and Hefei and Wuhan have encountered a decline. The observed spatial heterogeneity underscores the intricate relationship between urban expansion and ecological shifts. This study reveals the spatiotemporal dynamics of China's urban expansion and its ecological impact, providing valuable insights and policy recommendations for fostering the harmonized development of urbanization and ecological preservation. [ABSTRACT FROM AUTHOR]

With the increasing uncertainty of urban development, urban shrinkage in the rapid urbanization process in China has become increasingly serious. While many studies have explored urban shrinkage from the economic and population perspectives, they often ignore the essence of the phased evolution of economic and population factors. Thus, this study introduces the theory of economic resilience into the field of urban shrinkage and constructs a theoretical method for identifying urban shrinkage by integrating economic resilience and population change to reveal the evolutionary trajectory of regional urban growth and shrinkage. The results show that urban economic resilience and population change in the Shanxi-Shaanxi-Inner Mongolia region (SSIMR) exhibit strong volatility, highlighting the importance of conducting urban shrinkage studies within specific crisis disturbance scenarios. In the context of the "new normal of the economy", the economic resilience of cities in the SSIMR has significantly declined, and the problem of economic recession is gradually intensifying. The population change trend of cities in the SSIMR is relatively stable, with population loss being a common problem in urban development in the area and its scope and intensity increasing daily. Urban development in the SSIMR is evolving from global growth to widespread shrinkage, with 56.67% of the cities experiencing relative shrinkage, showing a spatial pattern of "western growth–eastern shrinkage". Factors such as the agglomeration effect, industrial structure, and policy system collectively shape the evolution of urban growth and shrinkage. [ABSTRACT FROM AUTHOR]

In the rapidly urbanizing world, as one of the distinct anthropogenic alterations of global climate change, global warming has attracted rising concerns due to its negative effects on human well-being and biodiversity. However, existing studies mostly focused on the difference in temperature elevation among urbanized areas and non-urbanized areas, i.e., rural or suburban areas. The allometric urban warming at intra-urban scales was overlooked. This research aimed to expand our understanding of urbanization–temperature relationships by applying a concept of a "previous-new" dichotomy of urbanized areas. To quantify the land surface temperature (LST) dynamics of 340 cities in China, we analyzed the LST of different land use types through trend analysis and absolute change calculation models. The urban heat island (UHI) effect of two spatial units, i.e., newly expanded urbanized area ("new UA" hereinafter) during 2000–2015 and previously existing urbanized area ("previous UA" hereinafter) in 2000, were compared and discussed. Our findings reveal that urban growth in China coincided with an LST increase of approximately 0.68 °C across the entire administrative boundary, with higher increases observed in regions between the Yellow River and Yangtze River and lower increases in other areas. Moreover, the new UA exhibited significantly greater LST increases and urban heat island intensity (HUII) compared to the previous UA. The dynamics of LST corresponded to the speed and scale of urban growth, with cities experiencing higher growth rates and percentages exhibiting more pronounced LST increases. This study reveals the impact of the underlying surface on human settlements on a large scale. [ABSTRACT FROM AUTHOR]

The concepts of healthy cities and smart cities are popular in emerging research in the 21st century. This study focuses on the existing interrelations between the two notions in terms of socio-spatial quality, technology, and innovation, particularly regarding industrial sites that no longer have a role and constitute 'urban voids' with high volumetric concentrations. The fast expansion of cities and the de-industrialization phenomena have resulted in such void-producing blights that compromise public health; environmental quality; and social, economic, and living conditions. Therefore, the authors intend to emphasize the relevance of citizens' and communities' engagement in shaping new healthy and smart urban environments. The present method relies on a literature review to describe the current theoretical and practical dimensions of such topics, identifying synergies and trade-offs. After this, a case study in China is presented to support the discussion. The site, a former granary, is located in Lianshi, a traditional water-edge town in the central area of the Yangtze River Delta. The proposed example enhances solutions that meet healthy and smart requirements, transforming the former industrial area into a social catalyst, acting as an effective motivator for urban development. One such theoretical approach is exemplified by a project that won a national architecture competition in 2018, the 'Taihu Cultural Heritage Rehabilitation Competition'. The latter is then validated through practical solutions in a real-world context by analyzing the 'Cuckoo' project developed in 2021 for the same area. Overall, the integration of healthy and smart elements is proposed by the authors as an effective method to achieve more holistic and sustainable city development from both theoretical and practical points of view. [ABSTRACT FROM AUTHOR]

As an important carrier of expanded urban spatial growth, new towns have been a "policy tool" for spatial production in the new era and have received long-term and constant attention from circles such as geography, planning, and economics. National new districts constitute a new regional space for China to implement the national strategy and promote the transformation of urban development mode. They are mutually reinforcing with their mother cities and hinterland provinces. Based on the geodetector method, this paper reveals the key factors driving the development of national new districts by mother cities and hinterland provinces and their interaction effects, which provides a basis for municipal and provincial governments to accurately formulate policies to promote the development of new towns by classification. The study shows that, firstly, there are five types of driving factors, that is, all-round driving factors, scale-increasing factors, expansion and quality-improving factors, expertise driving factors, and non-driving factors. The strength and dimension of the driving factors are characterized by prominent heterogeneity; R&D personnel, export and import trade are the key factors to expand the increment, optimize the inventory, and improve the quality; the overall development driving forces are in the order of innovation > opening > industry > investment > population. Secondly, the pairwise interaction between different factors exhibits two-factor enhancement, and the population shows a nonlinear increase in the driving force of investment, openness, and innovation on a provincial scale. Thirdly, according to the driving force of the factors and the interaction between them, suggestions are put forward based on the development stage and key demands for city and provincial governments to make policies for the development of national new districts, to support the establishment of scientific competition and cooperation between new towns and mother cities or regions, and to build a long-term collaborative development mechanism. [ABSTRACT FROM AUTHOR]

Since the reform and opening up, China's urbanization level has increased rapidly, with the urbanization rate rising from 17.92% in 1978 to 63.89% in 2020. At the same time, the extreme expansion of urban space has gradually become a common phenomenon, and the problem of urban sprawl has become a stumbling block to the high-quality development of Chinese cities. The traditional single-indicator method and multi-indicator method have obvious shortcomings in the richness of index dimension and the subjectivity of indicator selection, respectively, when measuring urban sprawl quantitatively. In this study, based on the weighted urban proliferation (WUP) model, we integrated the three independent dimensions of urban permeation (UP), dispersion of built-up areas (DIS), and utilization density (UD) to verify the applicability and feasibility of the model for quantifying the spatiotemporal pattern of urban sprawl, taking the Bohai Rim region in China as an example. There were four main results. Most cities in the Bohai Rim region had a moderate-to-high level of urban sprawl, with obvious spatial heterogeneity by province. The average WUP of cities in the Bohai Rim region increased by 61.83% from 2000 to 2020, and cities with moderate urban sprawl became cities with high sprawl. The urban sprawl process in the Bohai Rim region accelerated during 2010−2015 and stabilized thereafter. The increase in WUP caused by the growth of built-up areas is the main driver of urban sprawl in the Bohai Rim region. This study found that the WUP model can be effectively applied to the Bohai Rim region of China, where it reflects the multidimensional features of urban sprawl and provides new insight into its spatiotemporal pattern. [ABSTRACT FROM AUTHOR]

Urban sprawl has become a notable feature in China. Previous studies have found that railway development has a significant effect on urban sprawl. However, the detailed mechanisms of how railways affect urban sprawl have not been studied in depth. Furthermore, China's railway system has already formed a network. The network status of cities within the railway network may affect urban sprawl, but few studies have examined this factor. In this context, to explore the effects of railway networks on urban sprawl and the mechanisms of these effects, this study applied the social network analysis (SNA) method to measure the indicators of railway network characteristics and conducted panel model regression with the above indicators using the data from 26 cities from 2011 to 2019 in the Yangtze River Delta (YRD) in China. The main conclusions are as follows: (1) Railway network construction has a significantly positive impact on urban sprawl through the network agglomeration and diffusion mechanisms. (2) The network agglomeration mechanism improves the location condition of the central cities on the railway network, which encourages urban sprawl as an agglomeration pattern. (3) The network diffusion mechanism enhances the integration of the peripheral cities with the central city on the railway network, which encourages urban sprawl as a diffusion pattern. The network diffusion mechanism is heterogeneous in metropolitan areas (MAs) for the different levels of central city agglomeration. The findings provide a reference for railway construction and urban planning. [ABSTRACT FROM AUTHOR]

Urban spatial morphology reflects the processes of external urban expansion and the internal spatial structure of the human economy, and exploring urban spatial morphology is important for regional management of PM2.5 pollutants in the air environment. Whether urban spatial morphology can influence air pollution is a question that has been explored and evaluated. Therefore, we constructed a spatial-temporal driving mechanism framework and explored the interactions among urban expansion and PM2.5 pollutants in the "2 + 26" cities of Beijing-Tianjin-Hebei (BTH). Based on 2010, 2015, and 2020 urban expansion factors and PM2.5 pollutants data from the "2 + 26" cities of BTH, the results of the Geo-Detector medal imply that: (1) The spatial distribution characteristics of areas with high PM2.5 pollutants in the "2 + 26" cities of BTH were affected by the PM2.5 concentration value, and the high-value phenomenon appeared to decrease with the improvement of PM2.5 pollutants. (2) The level of urbanization in the "2 + 26" cities of BTH had been increasing annually, with the most significant growth in construction land area located in the northeastern coastal cities. (3) The compactness index, was the most critical influencing urban expansion factor, explaining 0.63, 0.64, and 0.66 of PM2.5 pollutants in 2010, 2015, and 2020. (4) In factorial interactions, the compactness index and the centrality ratio explained spatial and temporal analysis characteristics of PM2.5 pollutants, and the interaction factor enhanced the explanation for the spatial-temporal characteristics. This study reveals the coupled spatial-temporal driving mechanism of air pollution in the "2 + 26" cities of BTH and also shows that reasonable urban planning has a positive impact on the regional ecological environment in the future. [ABSTRACT FROM AUTHOR]

Disasters caused by climate change are continuing around the world. Densely populated urban areas have been pushed to the forefront of global climate change, and ecological security has gradually become the focus of global attention. Whether it is predictable natural disasters, or it is long-term global warming, or any unexpected events, exploring green development that coexists with them, green urban environmental strategies will play an important role in urban development. We analyzed data from 31 sample cities in China, accurately quantified indicators through qualitative and quantitative analysis, and then explored the development status and related indicator systems of green cities in China by "Driving Force–State–Response" model. The results reveal that (1) economic factors are the fundamental and decisive factors for the development of green cities. The higher the level of economic development, the stronger the ability of urban development; we also revealed the indicators that are significantly correlated with the level of green city construction and clarified the important factors of green cities; (2) technological factors are crucial for the construction of green cities. Only with continuous improvement at the technological level do green industries have the driving force for sustainable development, and traditional high-energy consuming and high-pollution industries can be continuously eliminated so as to promote the construction of green cities. (3) Based on the correlation analysis between each indicator and comprehensive scores, this study also pointed out that there is a significant gap in the level of green city construction among different regions in China. [ABSTRACT FROM AUTHOR]

The smart city is recognized as a potent instrument for creating efficient urban environments and improving the quality of life of urban residents. However, there is an absence of research establishing a comprehensive evaluation model for the smart cities (SCs) and focusing on their spatiotemporal analysis. Thus, a comprehensive evaluation framework was developed and applied to 26 cities in the Yangtze River Delta Urban Agglomeration (YRDUA) in China from 2017 to 2020 to assess the smart city level (SCL) in China and analyze these cities' spatial–temporal characteristics. The results indicated the following: (1) The overall SCL in the YRDUA has exhibited sustainable improvement, and the gap between cities is gradually narrowing. (2) The SCL of the YRDUA exhibits a higher SCL in the east and a lower SCL in the west of the YRDUA. The global spatial correlation of the SCL was random. Nantong, Hefei, Jiaxing, Zhoushan, Chizhou, Tongling, and Wuhu showed significant local spatial correlation. (3) The comprehensive evaluation framework is applicable for analyzing the SCs in China, and this framework can also be extended to other countries. Pertinent recommendations are put forth to enhance the SCL through the formulation of policies and fostering intercity collaboration. This research not only enriches the theoretical research on smart city evaluation but also clarifies the spatial–temporal characteristics of the SCs in China, thereby providing valuable insights that can foster sustainable smart city development. [ABSTRACT FROM AUTHOR]

This study investigates the development trend of smart-green cities, focusing on seven megacities in China. It addresses three issues that are common in urban green development, including the relationship between "smart" and "green", the scenario analysis of green development, and the uniqueness of megacities in green development. System dynamics modeling is applied. The simulation results reveal an "S"-shaped development curve for both aspects, indicating a gradual and accelerating growth pattern. Notably, the curve representing energy consumption lags behind the curve for smart city development by approximately three years. After 2030, when the smart city construction is expected to be completed, the proportion of the tertiary industry and investment in science and technology will play a significant role in limiting energy consumption. This study concludes by providing policy suggestions, including the need for long-term plans with phased targets, considering the specificity of megacities, and addressing external influences. [ABSTRACT FROM AUTHOR]

This study examines the relationship between urbanization, economic growth, industrial transformation, technological change, public services, demographical change, urban and natural environmental changes, and carbon emissions using a dataset of 182 prefecture-level cities in China between 2001 and 2010. Specifically, this paper differs from previous studies in two aspects. First, the extant literature has focused on how economic processes accompanying rapid urbanization affect carbon emissions in urban areas but gives little attention to the other dimensions of urbanization, including social and environmental changes, which may have important effects on carbon emissions. We assessed the effects of 17 key processes accompanying urbanization in a full range of economic, social, and environmental dimensions on carbon dioxide emissions in urban areas. The results showed that social processes accompanied with rapid urbanization had distinct effects on carbon emissions, compared to economic and environmental processes. Specifically, improvement in public services, indicated by education and cultural developments, reduces the increase in carbon emissions during urbanization, while economic growth and urban construction reinforces the growth in carbon emissions. Second, we examined the impact of various urbanization processes on carbon dioxide emissions using a unique dataset of 182 prefecture-level cities that covers a wide span of regions in China. The results of our analyses on the city level have important implications for the formulation of comprehensive policies aimed at reducing carbon dioxide emission in urban areas, focusing on different urbanization processes in economic, social, and environmental phases. [ABSTRACT FROM AUTHOR]

The combination of digital finance and financial inclusion can better meet the needs of those who have little access to financial services. This paper investigated the differences in the determinants and mechanisms of digital financial inclusion development between urban and rural areas. The sample consists of 1607 counties in China from 2014 to 2019, and uses the fixed-effect model and panel threshold technique. The empirical results indicate that: (1) The industrial economy and governmental intervention are the common determinants of urban and rural digital financial inclusion development, in which the degree is different. At the same time, secondary education is only a determinant in rural areas. (2) Industrial upgrading and indirect finance play a mediating role in the determinants of digital financial inclusion, but indirect finance is only significant for urban areas. (3) There is a threshold effect in the financial development-digital financial inclusion relationship. Under different financial development levels, the determinants of urban and rural digital financial inclusion show the discrepancy. With the development of digital financial inclusion under the trend of promoting innovative digital finance in China, these findings are expected to enhance access to financial services in urban and rural areas for more inclusive and sustainable futures. [ABSTRACT FROM AUTHOR]

Innovation networks promote regional innovation and economic growth. Using the patent data of cooperative inventions and the panel data of socio-economic statistics for 2010–2019, this study quantitatively analyzes the spatial structure evolution of intra-city and inter-city innovation networks for 41 cities in the Yangtze River Delta and their influence on economic growth. This study shows that these networks are increasingly connected and have a highly similar Z-shaped spatial structure. City economic growth is generally high, relatively stable, and mainly positively influenced by inter-city innovation networks. Intra-city innovation networks have no significant effect on economic growth; however, they are complementary to the inter-city ones. [ABSTRACT FROM AUTHOR]

Effective land use contributes to sustainable urban development. However, there are various reports suggesting that urban land resources used mismatch to different extents in many Chinese cities. This study measures the degree of the mismatch phenomenon in utilizing urban land resources from a supply–demand perspective, and a mismatching coefficient, namely land resource mismatch (LRM), is adopted as the measurement. The data used for the empirical analysis are from a sample of 35 cities in China. The empirical study shows the effectiveness of employing the mismatching coefficient LRM model in evaluating the degree of the mismatch phenomenon in utilizing urban land resources. The research findings suggest the following: (1) Overall, the mismatch phenomenon in utilizing urban land resources is significant in China in the form of either supply shortage or over-supply. (2) The degree of the mismatch phenomenon is different between different types of land, with the land for administration and public services showing more serious mismatching and the land for commercial and business facilities showing less mismatching. (3) There are significant differences both in the type and the degree of land use mismatch among different cities, which are contributed largely by the intensity of local government's controlling and planning role on land resources and the maturity of applying market mechanisms. The results from this study can inform the government of the importance and necessity of adopting effective policy measures for mitigating the mismatch phenomenon in utilizing urban land resources. The research method applied in this study can be applied in a larger context internationally for understanding the effectiveness of utilizing urban land resources. [ABSTRACT FROM AUTHOR]

Under the threat of global climate change, China has proposed a dual carbon goal of peak carbon and carbon neutrality. As the vital carrier for territorial spatial planning, production–living–ecological (PLE) spaces drive carbon emissions and are important to the dual carbon goals. In this study, carbon emissions and sinks of PLE spaces in cities in Heilongjiang Province from 2005 to 2020 were calculated and spatial–temporal changes were analyzed. The carbon emission structure was analyzed in segmentation sectors. The land use changes and socioeconomic factors on carbon emissions were analyzed, and emission reduction strategies were implemented. The results show the following: (1) Carbon emissions from production and living spaces increased yearly. Carbon sinks were smaller than emissions, but capacity was stable. (2) Higher-emission cities were concentrated in southwest Heilongjiang, and carbon emission differences between regions gradually increased. (3) Among carbon emission sectors, agricultural and household made up smaller proportions, while animal husbandry, industrial, transportation, and traffic travel contributed most. Carbon emission structures were transformed by adjusting urban development and industrial structure. (4) For most cities, industrial space was the main emission space, but agricultural production and urban–rural living spaces dominated in some cities. (5) GDP, urbanization rate, and area of city paved roads suppressed emissions in cities with decreased carbon emission grades. The industrial structure and coal consumption inhibited emissions in cities with maintaining and increasing carbon emissions grades. [ABSTRACT FROM AUTHOR]

As an effective measure to solve the dilemma of urban energy consumption and economic development, the new energy demonstration city (NEDC) policy in China could greatly promote the development of the new energy industry and urban economy. This study aims to explore how the NEDC policy effectively promotes the growth of urban land use efficiency (ULUE), an essential indicator of economic development, through the urban industrial structure. Based on the panel data of 285 Chinese cities during 2003–2019, this study took the NEDC policy as a quasi-natural experiment and employed the PSM-DID method and the mediating effect model to objectively evaluate its policy effects. We found that the NEDC policy could significantly promote the growth of the ULUE. Specifically, the ULUE has been significantly improved by 17.0%. The NEDC policy could also promote the ULUE indirectly through the mediating effect of industrial structure advancement (ISA), but the mediating effect of industrial structure rationalization (ISR) was not significant. Furthermore, the promotional effect of the NEDC policy on the ULUE has regional heterogeneity. Compared with eastern cities and high-innovation cities, central and western cities and medium-innovation and low-innovation cities can obtain much higher promotion effects. This study may provide some policy inspiration for policymakers to support low-corban and sustainable economic development and urban land use. [ABSTRACT FROM AUTHOR]

Accurately identifying the boundary of urban clusters is a crucial aspect of studying the development of urban agglomerations. This process is essential for comprehending and optimizing smart and compact urban development. Existing studies often rely on a single category of data, which can result in coarse identification boundaries, insufficient detail accuracy, and slight discrepancies between the coverage and the actual conditions. To accurately identify the extent of urban clusters, this study proposes and compares the results of three methods for identifying dense urban areas of three major agglomerations in China: Beijing–Tianjin–Hebei, the Yangtze River Delta, and the Guangdong–Hong Kong–Macao Greater Bay Area. The study then integrates the results of these methods to obtain a more effective identification approach. The social economic method involved extracting a density threshold based on the fused nuclear density of socio-economic vitality data, including population, GDP, and POI, while the remote sensing method evaluated feature indices based on remote sensing images, including the density index, continuity index, gradient index, and development index. The traffic network method utilizes land transportation networks and travelling speeds to identify the minimum cost path and delineate the boundary by 20–30 min isochronous circles. The results obtained from the three methods were combined, and hotspots were identified using GIS overlay analysis and spatial autocorrelation analysis. This method integrates the multi-layered information from the previous three methods, which more comprehensively reflects the characteristics and morphology of urban clusters. Finally, the accuracy of each identification result is verified and compared. The results reveal that the average overall accuracy (OA) of the three areas delineated by the first three methods are 57.49%, 30.88%, and 33.74%, respectively. Furthermore, the average Kappa coefficients of these areas are 0.4795, 0.2609, and 0.2770, respectively. After performing data fusion, the resulting average overall accuracy (OA) was 85.34%, and the average Kappa coefficient was 0.7394. These findings suggest that the data fusion method can effectively delineate dense urban areas with greater accuracy than the previous three methods. Additionally, this method can accurately reflect the scope of urban clusters by depicting their overall boundary contour and the distribution of internal details in a more scientific manner. The study proposes a feasible method and path for the identification of urban clusters. It can serve as a starting point for formulating spatial planning policies for urban agglomerations, aiding in precise and scientific control of boundary growth. This can promote the rational allocation of resources and optimization of spatial structure by providing a reliable reference for the optimization of urban agglomeration space and the development of regional spatial policies. [ABSTRACT FROM AUTHOR]

Exploring the effect of new-type urbanization (NTU) on urban carbon abatement is of great practical significance for promoting urban green construction and coping with the challenge of global climate change. This study used data from 250 cities in China from 2008 to 2020 and constructed the NTU evaluation indicator system from five dimensions. We used classical panel regression models to examine the effects of NTU on urban CO2 emissions, and further used spatial econometric models of SEM, SAR, and SDM to identify the spatial spillover effects of NTU on urban CO2 emissions. The main results are that China's NTU and CO2 emissions are generally rising, and NTU has a significantly negative effect on urban CO2 emissions, with an impact coefficient of −0.9339; the conclusions still hold after subsequent robustness tests. Heterogeneity analysis reveals that NTU's carbon abatement effect is more pronounced in resource-based cities, old industrial areas, and cities with lower urbanization levels and higher innovation levels. Mechanism analysis shows that improving urban technological innovation and optimizing resource allocation are important paths for realizing urban CO2 emission reduction. NTU's effect on urban CO2 emissions has a noticeable spatial spillover. Our findings provide policy makers with solid support for driving high-quality urban development and dual-carbon targets. [ABSTRACT FROM AUTHOR]

Since China is the largest developing country in the world, its urban reconstruction has significance for countries undergoing rapid urbanization. The recent development of its central cities has gradually changed from large-scale incremental expansion to stock optimization. District boundary reorganization has become a new trend in reforming China's administrative division of central cities. From the perspective of scalar reorganization and regional reconstruction, the adjustment of urban administrative divisions can be regarded as a regional construction strategy initiated by city governments to reshape the spatial structure, improve the governance relationship, and enhance the cities' competitiveness. This study takes Hangzhou, an important central city in eastern China, as a case study to illustrate two ways in which a central city can optimize its urban spaces through district boundary recombination: scale recombination and regional recombination. The findings demonstrate two advantages of district boundary reorganization for China's central cities: it eases the integration of new city districts and urban areas and promotes balanced development within the city. In the future, more Chinese cities will likely choose to reorganize their district boundaries. [ABSTRACT FROM AUTHOR]

The study of border resilience is an effective means to analyze the development status of border cities. This study constructs a border city resilience assessment framework, measures the urban resilience level of 13 prefecture-level administrative regions in China's northeastern border region from 2010 to 2019, reveals their temporal and spatial differentiation characteristics, analyzes the main obstacles, and proposes development strategies. This study reveals the following: (1) The overall resilience of the northeast border cities is at a medium level, and differences between regions and cities are large. (2) The resilience of the northeast border cities increased rapidly between 2010 and 2015, especially in the western area; the improvement effect was poor between 2015 and 2019, and except for the increased resilience of individual cities in the eastern area, the development of other cities was slow and some even declined. (3) At the city scale, the development potential, economic structure, residents' security, and environmental governance capabilities are the main factors restricting improvement in the basic resilience of the northeast border cities. Insufficient national policy support and the poor development of neighboring countries have become obstacles to cities' exclusive resilience. [ABSTRACT FROM AUTHOR]

Timely and rapidly mapping impervious surface area (ISA) and monitoring its spatial-temporal change pattern can deepen our understanding of the urban process. However, the complex spectral variability and spatial heterogeneity of ISA caused by the increased spatial resolution poses a great challenge to accurate ISA dynamics monitoring. This research selected Jinan City as a case study to boost ISA mapping performance through integrating the dual-attention CBAM module, SE module and focal loss function into the Deeplabv3+ model using Sentinel-2 data, and subsequently examining ISA spatial-temporal evolution using the generated annual time-series ISA data from 2017 to 2021. The experimental results demonstrated that (a) the improved Deeplabv3+ model achieved satisfactory accuracy in ISA mapping, with Precision, Recall, IoU and F1 values reaching 82.24%, 92.38%, 77.01% and 0.87, respectively. (b) In a comparison with traditional classification methods and other state-of-the-art deep learning semantic segmentation models, the proposed method performed well, qualitatively and quantitatively. (c) The time-series analysis on ISA distribution revealed that the ISA expansion in Jinan City had significant directionality from northeast to southwest from 2017 to 2021, with the number of patches as well as the degree of connectivity and aggregation increasing while the degree of fragmentation and the complexity of shape decreased. Overall, the proposed method shows great potential in generating reliable times-series ISA data and can be better served for fine urban research. [ABSTRACT FROM AUTHOR]

The supply of built-up land determines the depths of human activities, leading to the differences in scale and intensity of carbon emissions. However, the relationship between the composition of built-up land and carbon emissions has not been fully investigated. In response, this study collects the panel data of 88 cities along the Yangtze River Economic Belt, China, and uses the fixed effect model and system GMM model, to explore the impacts of specific subtypes of built-up land on carbon emissions averaged by economic output and urban land. The findings show that industrial land and commercial land are the main contributors to increase carbon emissions; the increased proportions of land subtypes related to supporting facilities and infrastructures show significant restraining effects; carbon emission was a dynamic process with time-lagged effects. As a result, reallocating the structure of urban built-up land can directly and indirectly adjust the intensity of carbon emissions. Policy recommendations focus on the balanced supplies of production and ecological land. [ABSTRACT FROM AUTHOR]

As the world's most populous country, China has experienced massive population growth and dramatic regional migration over the past 30 years. From 1990 to 2020, the national population increased by 24.4%, the urban population tripled, and the rural population declined by 41.0%. Combined with complex topographic features, unique characteristics of the population distribution have emerged. Many studies have examined changes in the spatial distribution of the population. However, few studies have examined the stability of certain aspects of this distribution over the last 30 years, particularly at the raster scale, which may provide important information for future research and development plans. Based on land use maps and nighttime light images, China's census data from 1990 to 2020 was scaled down to a resolution of 1 km using a method called multiple linear regression based on spatial covariates. The results show that there were some striking features of both stability and change in the spatial distribution of China's population over the past three decades. The population shares divided by the Hu line, the Qinling-Huaihe line, and the three-step staircase have remained almost unchanged. In contrast, the population share of the coastal region has risen from 23.7% to 29.0% during the study period. The urban areas have expanded by 1.35 times and their population has doubled. In addition, for every 1 km2 increase in the urban areas, an area of 29.4 km2 has been depopulated on average. This suggests that urbanization can alleviate population pressure in larger areas. However, the coastal regions and urban and peri-urban areas were the main areas of population density growth, so they required a great deal of attention for ecological protection. [ABSTRACT FROM AUTHOR]

With in-depth efforts in the national strategy of innovation-driven development, the demand for talent in cities is burgeoning. Cities in China have released a large number of preferential policies to attract talent as these cities look to gain an edge in increasing talent competition. This study empirically studied the effect of talent competition on urban innovation using a panel data set of 298 prefectural-level cities in China from 2010 to 2019 based on the difference-in-difference model and an event study method. The results show that there are heterogeneous effects of talent competitions on urban innovation, which may widen the gap between urban innovation in different cities. The effect of talent competition in different cities showed a significant positive correlation with the level of urban development, and there is a "head effect" of talent competition on urban innovation. Moreover, the results of the mechanism analysis indicate that the effect of talent competition on urban innovation is mainly through talent flow. These findings can help policymakers formulate scientific and reasonable talent policies to promote the strategy of innovation-driven development. [ABSTRACT FROM AUTHOR]

With rapid urban population growth and industrial agglomeration, the urban land supply is becoming gradually tight. Improving land use quality (LUQ) is becoming increasingly critical. This study was carried out in the Luohe built-up zones between 2013 and 2021. The aim is to explore the growth characteristics of LUQ and determine the association between the inner urban location and the growth rate from the perspective of spatial heterogeneity. Therefore, based on a socio-economic-environmental framework, we selected an integration/GDP/population/artificial-surface Rate, and a remote-sensing-based ecological index to construct a LUQ assessment framework that is more stable and applicable for developing urban areas. Additionally, then, multiscale geographical weighted regression is adopted, which can better help us explore the scale of the location factors. The results show that: (1) The LUQ overall growth is gradually slowing. High-quality areas clustered in the urban center and subsystem elements spread outward along the national and provincial highways to drive boundary expansion; (2) In the W/E/SE direction, land use tends more towards physical sprawl than usual development and expansion; (3) Location factors were distinguished as global, semi-global, and local. The global factors constitute the homogenized locational space. Semi-global and local factors constitute a heterogeneous locational space. The latter is critical to guide LUQ growth. LUQ assessment can promote intensive land use. Exploring location factors can further guide the LUQ spatial growth and provide data in support of urban planning. [ABSTRACT FROM AUTHOR]

As the main carbon sink in the carbon cycle process, vegetation is an important support for achieving "carbon peaking" and "carbon neutrality. How does the vegetation coverage of urban built-up areas change in the process of urbanization in China? Taking advantage of Landsat remote sensing data, we extract urban built-up areas, calculate the Normalized Difference Vegetation Index (NDVI), estimate fractional vegetation cover (FVC), and analyze the temporal and spatial dynamics of vegetation coverage in built-up areas of provincial capitals from the national and individual city levels in China. Major conclusions are as follows: (1) The FVC in the urban built-up areas has increased by 7.97%, and the urban green space has gradually changed from the "green core" distribution model to the "green vein" distribution mode. (2) The disparities in FVC of built-up areas of provincial capitals are notable, presumably due to a variety of factors that include the natural geographic environment, economic development level, built-up area expansion, land type conversion, afforestation of greening policy, etc. (3) Not just simply raise or lower, the FVC curves in the built-up areas of provincial capital cities present oscillating patterns with gradually weakening amplitude. Our study is expected to provide scientific references of an important theoretical basis for urban ecological construction and practical support for promoting the harmonious development of urban residents and urban environments in China. [ABSTRACT FROM AUTHOR]

The urban heat island ( U H I ) refers to the land surface temperature (LST) difference between urban areas and their undeveloped or underdeveloped surroundings. It is a measure of the thermal influence of the urban built-up area expansion ( U B A E ), a topic that has been extensively studied. However, the impact of U B A E on the LST differences between urban areas and rural areas ( U H I U − R ) and between urban areas and emerging urban areas ( U H I U − S ) in different seasons has seldom been investigated. Here, the U H I U − S and U H I U − R in 34 major metropolitan regions across China, and their spatiotemporal variations based on long-term space-borne observations during the period 2001–2020 were analyzed. The U B A E quantified by the difference in landscape metrics of built-up areas between 2020 and 2000 and their impact on U H I was further analyzed. The U B A E is impacted by the level of economic development and topography. The U B A E of cities located in more developed regions was more significant than that in less developed regions. Coastal cities experienced the most obvious U B A E , followed by plain and hilly cities. The U B A E in mountainous regions was the weakest. On an annual basis, U H I U − R was larger than U H I U − S , decreasing more slowly with U B A E than U H I U − S . In different seasons, the U H I U − S and U H I U − R were larger, more clearly varying temporally with U B A E in summer than in winter, and their temporal variations were significantly correlated with U B A E in summer but not in winter. The seasonal difference in U H I U − R was larger than that of U H I U − S . Both the U H I U − S and U H I U − R in coastal cities were the lowest in summer, decreasing the fastest with U B A E , while those in mountain cities decreased the slowest. The change in the density of built-up lands was the primary driver affecting the temporal variations in U H I U − S and U H I U − R during U B A E , followed by changes in proportion and shape, while the impact of the speed of expansion was the smallest, all of which were more obvious in summer than in winter. The decreased density of built-up lands can reduce U H I . These findings provide a new perspective for a deeper understanding of the effect of urban expansion on LST in different seasons. [ABSTRACT FROM AUTHOR]

The expansion of urban built-up areas is one of the most prominent characteristics of land use change in China. A growing body of literature has emphasized the triple spatial effects of the administrative hierarchy on urban built-up areas expansion, including heterogeneity, radiation, and segmentation. However, the existing studies have mainly focused on the administrative hierarchy at the prefectural level and above and have primarily concentrated on one single effect; few have integrated the triple effects as a whole. Based on high-resolution land use data and taking Fujian province as a study case, this study proposes an integrated theoretical framework and modeling approach and investigates the triple spatial effects of administrative hierarchy on built-up areas at the prefectural level and below. Descriptive statistics show the following: (1) Built-up areas of municipal districts are significantly larger than those of county-level units, showing the heterogeneity characteristics of urban land distribution across different levels of administrative hierarchy; (2) The county-level units adjacent to municipal districts exploit more built-up areas than other county-level units, indicating the radiation effects of municipal districts; (3) The radiation effects tend to be reduced if a municipal district and its adjacent county-level units are not located in the same prefectural city, revealing the segmentation effects among the different prefectural cities. Using the spatial econometric model with regimes, we further find the following: (1) The strengths of driving forces of built-up areas are heterogeneous between municipal districts and county-level units, and there are significant spatial interactions among administrative units; (2) The spatial interactions between municipal districts and county-level units are stronger than those between two county-level units, but the strength is restricted by the prefectural boundary, reflecting the radiation effects of municipal districts and the segmentation effects of the prefectural boundary, respectively. By investigating the triple spatial effects of the administrative hierarchy on urban built-up areas, we conclude that comprehensively considering these triple effects as a whole will result in a fuller understanding of the rapid built-up areas expansion in China, especially at the prefectural level and below. [ABSTRACT FROM AUTHOR]

With accelerated urbanization and rapid expansion of the urban population, there is an increasing demand among urban residents for urban green spaces (UGS) and the ecosystem services (ES) they provide. The existing research mostly focuses on the spatial pattern of UGS types and ES provided by different UGS but ignores that residents' preferences for UGS types and their ecological and social services should also be incorporated into the spatial planning decision-making of UGS. A web-based questionnaire was distributed randomly in urban areas of China and 1050 valid samples were collected in this study. Descriptive statistical analysis methods, structural equation modeling, and Pearson correlation were used to parse the residents' preference for both UGS types, ecological–social services, and the relevant impact factors. The results showed that: (1) the strongest preference of residents for UGS and their ecological and social services are the attached green space, "beautifying the city", and "physical and mental relaxation", respectively; (2) the leading factors for residents' access to UGS are "age" and "sufficient time", except for attached green space. The most significant effect on both ecological and social services is the "season" factor. Further, "social gathering" and "exercise" are the services most and least likely to be affected. (3) Future planning of UGS should reinforce construction of attached green space and improve the aesthetics-related ES they provide. Construction of park green space and plaza green space should be enhanced to deal with the aging trend in society. Further, maintaining the existing construction of attached green space and building regional green space are crucial to the sustainability of UGS and its ecological–social services. [ABSTRACT FROM AUTHOR]

The growth and shrinkage of cities and towns are normal phenomena in the evolution of regional town systems. The growth and shrinkage of different levels of cities and towns are mutually influential. This study uses ArcGIS and the Hierarchical Linear Model to analyze the hierarchical differences and correlations in the characteristics and mechanisms of shrinking cities and towns in Northeast China from 2000 to 2020. The results indicate that the shrinkage of cities and towns is characterized by hierarchical differences. High-level cities show widespread and slight shrinkage, while low-level towns show the most severe and continued shrinkage. The population shrinkage of cities and towns within the same municipality is not fully synchronized. In terms of spatial patterns, the multi-level relationship between cities and towns is divided into growth-driven, central siphon, peripheral growth, local growth, and global shrinkage. The shrinkage of high-level cities is mainly influenced by economic and industrial development and built-up environment. The shrinkage of low-level towns is constrained by population concentration, economic development, enterprise scale, local arable land resources, and environmental quality. Wages, jobs, and infrastructures in high-level cities have a strong siphoning effect on low-level towns, while technology and industrial development drive the population and economic development of low-level towns. [ABSTRACT FROM AUTHOR]