Spatial Structure In China Research Articles

The Carbon Emission Reduction Effect and Spatio-Temporal Heterogeneity of the Science and Technology Finance Network: The Combined Perspective of Complex Network Analysis and Econometric Models

With the active promotion of the “carbon peaking and carbon neutrality” goals, science and technology finance (STF) is the important driving force of low-carbon development, and financial networks facilitate the aggregation and transformation of resources in space, so it is of great theoretical and practical significance to investigate the impact of science and technology finance networks (STFN) on carbon emissions (CE). Based on the 30 provinces of China from 2011 to 2019, this article used the STF development level in each province as the main indicator to construct the STFN. The complex network analysis and econometric models are combined, with the weighted degree values and betweenness centrality selected as typical network structure indicators incorporating into the econometric model to explore their impact on CE. Then, the Geographically and Temporally Weighted Regression (GTWR) model is applied to analyse the spatio-temporal heterogeneity of influencing factors. The results show the following: (1) From 2011 to 2019, the spatial structure of China’s STFN has changed significantly, and the status of the triangle structure consisting of Beijing–Tianjin–Hebei (BTH)–Yangtze River Delta (YRD)–Pearl River Delta (PRD) is gradually consolidated in the overall network, and the network structure tends to be stable. (2) The results of the benchmark regression show that the weighted degree value of the STFN has a significant inhibitory effect on CE, while betweenness centrality shows a certain positive effect on CE. (3) The weighted degree value has a more significant effect on CE reduction in the eastern region, while the betweenness centrality has a more significant effect on CE reduction in the central and western regions, but shows a significant promotion effect in the eastern region. (4) There is spatio-temporal heterogeneity in the effects of residents’ affluence, energy consumption, industrial structure, and environmental pollution on CE.

Research on Carbon Emission Characteristics and Differentiated Carbon Reduction Pathways in the Yangtze River Delta Region Based on the STIRPAT Model

With the changes in the spatial structure of China’s economic development, urban clusters have become the primary carriers of China’s regional economy and green growth. We used annual data from 2010 to 2021 to study the carbon emission characteristics and carbon reduction pathways of 36 cities in the Yangtze River Delta region. Firstly, based on the decoupling elasticity coefficient and carbon intensity index, the researchers divided the cities in the Yangtze River Delta into six types of carbon emissions. Then, the STIRPAT model was used to regress the panel data of different carbon emission types for 11 years, analyze the driving factors of carbon emissions, and develop differentiated carbon emission reduction paths for cities with six carbon emission types. According to the results, the cities of Type I need to accelerate low-carbon technology innovation; the cities of Type II need to improve energy efficiency and strengthen low-carbon technology research and development; the cities of Type V need to suppress foreign investment in high-energy consumption and high-emission projects in the local area; the cities of Type VI need to accelerate the process of new urbanization and optimize industrial structure. However, the researchers found that the cities of Types III and IV have not yet received effective emission reduction pathways, and their emission reduction policies and measures need to be further studied.

City-level environmental performance and the spatial structure of China's three coastal city clusters

Cities' environmental efficiency (measured in terms of green total factor productivity, GTFP) have been found in the existing literature to correlate spatially. However, the spatial structure of the interrelations between cities' GTFP have not yet been determined. In this study, we attempted to characterize city-level spatial networks of GTFP by investigating China's major three coastal city clusters: Jing-Jin-Ji (JJJ), Yangtze River Delta (YRD), and Pearl River Delta (PRD). We estimated the GTFP of 38 cities within these three coastal city clusters by applying a super-efficiency slack-based measure (SBM) within a data envelopment analysis (DEA) approach, constructed a spatial network of GTFP for each city cluster based on gravity model, traced out the centralities and subgroups of each GTFP network by conducting social network analysis, and then investigated the socioeconomic factors correlating to GTFP interrelation between cities. The results are as follows: First, the average GTFP in the three clusters increased from 2010 to 2021, as did the industrial value added in these regions. In addition, average GTFP increased the most in PRD region relative to the other two clusters. Second, centers of the spatial network of GTFP exist in these three regions. These are as follows: Beijing, Tianjin, and Langfang in JJJ region; Wuxi, Suzhou, and Yangzhou in YRD region; and Guangzhou and Foshan in PRD region. In the JJJ and YRD regions, the composition of the subgroups containing cities with greater closeness of GTFP underwent significant changes between 2010 and 2021, whereas the composition of the subgroup in the PRD region did not change as much. Third, differences in terms of industrial structure and distance between two cities are key underlying factors that influence the interrelation of GTFP between these cities. The characteristics of the spatial networks of GTFP in the three city clusters imply that improving the balance between the central cities and other noncentral cities to alleviate the misallocations between cities and economic resources could result in an increase in the overall efficiency of economic growth and environmental improvement.

Exploring the impact of changing landscape patterns on ecological quality in different cities: A comparative study among three megacities in eastern and western China

The landscape pattern emerges from the intricate interplay among natural, biological, and social elements, profoundly influencing the quality of the regional ecological environment. By comparing the spatial and temporal driving mechanisms of landscape pattern changes on ecological environment quality across various cities, we can gain valuable insights into charting sustainable development paths for cities in the future. The results show that: (1) From 1990 to 2020, the mean RSEI values for Kunming and Nanjing exhibited a certain degree of increase, suggesting an improvement in ecological quality over time. Conversely, Guangzhou displayed relatively high and stable ecological quality throughout the studied period. (2) The CA-Markov results reveal minimal variations in the ecological quality of Kunming by 2035. Conversely, Nanjing experiences a decline in ecological quality, while Guangzhou demonstrates commendable achievements in ecological development, with an area accounting for moderate or higher ecological grades reaching 71.13%. (3) During the 30 years, the polarization of the three cities intensified and gradually formed a polycentric and clustered urban form. Among them, Nanjing and Guangzhou showed a fragmented landscape pattern, while the landscape diversity of Kunming is decreasing. (4) In terms of landscape pattern changes, Nanjing and Guangzhou showed a fragmented landscape pattern and increased landscape heterogeneity, but the degree of fragmentation and the rate of urban expansion in Guangzhou have been mitigated. In contrast, the spatial distribution of landscape patches in Kunming is becoming more clustered and the landscape diversity is decreasing. (5) The results of MGWR show that improving the landscape diversity, landscape patch aggregation and connectivity is beneficial to improving ecological quality. Overall, this study provides valuable insights and serves as a relevant reference for optimizing urban spatial structure in China and other developing countries' cities, aiming to foster sustainable and ecologically conscious urban development.

Analysis of the China’s Interprovincial Innovation Connection Network Based on Modified Gravity Model

With the arrival of the era of innovative economy, innovation is of great significance for the development of China, and even the world. Based on statistical data and taking 2009, 2014, and 2019 as node years, this study uses the entropy weight method and a modified gravity model to study the pattern and evolution characteristics of China’s interprovincial innovation network. The results showed that: 1. The weights of innovation output, innovation input, and innovation environment were 0.253, 0.340, and 0.407, respectively. Currently, innovation output is the most representative of the interprovincial innovation connections, but the weight of innovation environment has been increasing year by year, and its importance is constantly highlighted. 2. The overall spatial structure of China’s interprovincial innovation network shows a “core periphery” feature, radiating from coastal provinces such as Jiangsu, Beijing, and Zhejiang to inland provinces, and exhibiting an overall pattern of “strong in the east and weak in the west”. 3. In terms of evolutionary characteristics, Guangdong and Jiangsu ranked in the top two in terms of outward innovation scale from 2009 to 2019. The combined total innovation connections of the top five provinces in 2009, 2014, and 2019 accounted for 70.79%, 64.29%, and 64.24%, respectively. Although the phenomenon of uneven innovation connections exists, it has slowed down. In addition, China’s interprovincial innovation network is gradually becoming enriched, with the most significant change being the number of innovation links, with a gravity level increasing from four in 2009 to twenty-six in 2019. The interprovincial innovation links continue to strengthen, but the focus has not changed significantly; it is still concentrated in the Bohai Rim region and the Yangtze River Delta region. 4. In terms of maximum gravitational lines, Guangdong Province had the highest number of maximum gravitational lines in 2009, 2014, and 2019, with a total of six. The maximum gravitational line change from 2009 to 2019 took place from 2014 to 2019, transitioning from “Jilin-Liaoning” to “Jilin-Heilongjiang”.

Spatially Structured Environmental Analysis of Marine Ecological Landscapes Based on Machine Vision

In this study, based on the current development status of Zhanjiang’s marine economy and ecological landscape environmental spatial structure in China, an appropriate coordination measurement model tailored to Zhanjiang’s marine economy and the ecological environment was selected. The spatially structured environment of marine ecological landscape (MEL) is analyzed based on machine vision (MV) technology. It established a subsystem for Zhanjiang’s marine economy and ecological landscape environmental spatial structure and chose relevant system indicators. Through data standardization, principal component analysis and regression fitting analysis, the spatial structured coordination degree of MEL is measured, and the marine economy and ecological environment are comprehensively analyzed, which is important for the future development of MEL. By charting the coordination degree trend over the years and conducting an empirical analysis of the comprehensive development level and coordination degree of Zhanjiang’s marine economy and ecological environment, policy recommendations are offered to encourage the harmonious development of Zhanjiang’s marine economy and ecological landscape environmental spatial structure.

Correction: Niu, F.; Wang, F. Economic Spatial Structure in China: Evidence from Railway Transport Network. Land 2022, 11, 61

In the original publication [...]

Spatial Structure of China’s Green Development Efficiency: A Perspective Based on Social Network Analysis

Clarifying the spatial correlation network structure of green development efficiency (GDE) is of great significance for realizing coordinated and sustainable development in China. By constructing the evaluation index system of GDE, this study used the super epsilon-based measure (EBM) model that considers undesirable output to measure the GDE of China from 2000 to 2018, based on which the characteristics of the spatial correlation network characteristics and influencing factors were analyzed using social network analysis (SNA) and a geographical detector. The results indicated that: (1) The GDE of China as a whole remained relatively stable, and there was a significant spatial spillover effect of GDE between provinces; the spatial correlation network demonstrated complex and dense characteristics, and the closeness and stability of the network gradually increased. However, the strict hierarchical structure of the network still existed. (2) The eastern coastal provinces exhibited significant spillover effects and connectivity functions, while the northeastern and central-western provinces are located at the edges of the spatial correlation network. (3) The GDE spatial correlation network is divided into a leader subgroup, bridge subgroup and net benefit subgroup, with no isolated subgroup. (4) The economic development level, urbanization and financial development have a decisive impact on the formation of the GDE spatial correlation network.

Spatial Structure of China’s E-commerce Express Logistics Network Based on Space of Flows

Spatial Structure of China’s E-commerce Express Logistics Network Based on Space of Flows

High-resolution accounting of urban emissions in China

The cities of China, the world’s largest CO2 emitting country, play a crucial role in mitigating global climate change by their pursuit of carbon neutrality. However, assessing their decarbonization levels with internationally recognized metrics such as the OECD cities’ criteria is a major challenge, as the fuzzy definitions of China’s cities – including by city administrative boundary (UB1), city district boundary (UB2), and urban built-up area (UB3) – create misconceptions and ambiguities over the integrity and accuracy of their reported emissions. In this study, we develop a new China high-resolution emission database (CHRED) as a means of quantifying urban emissions based on dynamic city limits defined by population density boundary (UB4). Employing a 1 km grid dataset built from point-emission sources, it is showed that: (1) the reported emissions from the adoption of different urban boundaries can have differences as large as 17.77 %; (2) the spatial structure of China’s urban CO2 emissions has a clustered pattern reflecting the country’s spatial urban agglomeration structure; (3) the CO2 emissions per capita of China mega UB4 cities are similar to OECD C40 cities; and (4) that nonindustrial emissions are influenced by geographical location and population density.We further argue that the boundaries of UB4 cities need to be continuously adjusted to reflect the growth of urban built-up land across China. This is further evidenced by a counterfactual estimation and scenario analysis, which indicates that the differences in per capita nonindustrial emissions under different scenarios of population growth and urban sprawl could be as large as 27.6 % by 2040. The findings show that a bottom-up accounting database based on the UB4 boundary is significant for building high-resolution urban emissions inventories to mitigate nonindustrial carbon emissions in China.

Evolution Characteristics and Formation Mechanism of Production-Living-Ecological Space in China: Perspective of Main Function Zones.

The main function zone (MFZ) is the major strategy of China’s economic development and ecological environment protection. Clarifying the logical relationship between “MFZ strategy” and “territorial spatial layout” is vital to construct regional economic layout and territorial spatial supporting system of high-quality development. However, few studies have revealed the evolution process and formation mechanism of the production-living-ecological space (PLES) structure of China’s MFZ over a long period of time. To bridge the gap, based on the land use dataset in China from 1980 to 2020, this study analyzed the evolution patterns of PLES in China’s MFZs using multiple methods and measured the formation mechanism of PLES in different types of MFZs with the GeoDetector model. Results showed that the spatial structure of China’s national territory has evolved drastically in the past 40 years, showing significant horizontal regional differentiation and vertical gradient differentiation. Ecological space has been continuously decreasing, while production space and living space have been continuously increasing, and the evolution of PLES varied significantly in different MFZs. During the study period, the gravity center of PLES in China all moved westward. The spatial distribution pattern of production space and living space was from northeast to southwest, and the ecological space was from east to west. The evolution of China’s territorial spatial structure was subject to the combined effects of natural and socio-economic factors, exhibiting significant differences in different MFZs. Land use intensity had the most prominent influence on the formation of PLES, followed by elevation. The influences of different factors on PLES structure were strengthened mainly through two types of nonlinear enhancement and dual-factor enhancement. This study can provide scientific support for the optimal management and high-quality development of territorial space in China.

Economic Spatial Structure in China: Evidence from Railway Transport Network

This study analyzes the structure of China’s overall railway transport network and its sub-networks of conventional railway and high-speed railway, with the aim to understand the country’s economic spatial structure that is reflected by or underlines the railway transport network. First, the results indicate that compared with developed cities, backward cities not only have fewer train services but also lack a symmetrical transport plan; backward cities tend to connect with developed cities rather than within themselves. Second, the national-level urban hierarchy was established using the proposed algorithm, which helped reveal the economic geography of three economic plates in China. Third, the law of the primate city is not prominent in a large country such as China, which is undergoing regional restructuring with the economic center of gravity shifting to the coastal area while also moving south.

The Evolution of the Urban Employment Spatial Structure in China: From the Perspective of Monocentricity and Polycentricity

The Evolution of the Urban Employment Spatial Structure in China: From the Perspective of Monocentricity and Polycentricity

The Spatial Structure Evolution of China's High-Speed Rail Network and Its Impacts on Real Estate Investment

The construction of China's large-scale high-speed rail (HSR) could exert a significant impact on the connectivity of urban networks in the long run. Through the dominance index of city nodes and the strength index of city links, the evolution of Chinese HSR networks has been explored based on frequency flow data from 2007 to 2017. Meanwhile, this paper uses a spatial econometric model to test the impact of the evolution of HSR networks on real estate investment agglomeration. Our examination shows that, as China's HSR network expands spatially, connectivity between cities improves, and the spatial structure of China's urban systems tends to be less hierarchical and polycentric. HSR networks promote the spatial agglomeration of real estate investment in cities connected by HSR. Although the influence of population scale, manufacturing scale, per capita GDP, and the degree of openness on real estate investment is greater than that of HSR network connection, the impact of the proportion of residential (commercial service) land and per capita GDP on real estate investment is less than that of HSR network connection. China's HSR network connection can expand the spatial agglomeration effect of site cities' real estate investment. The urban land use structure, such as the proportion of residential (commercial) land and the degree of openness, can promote a spatial spillover effect of real estate investment.

How Does Urban Spatial Structure Affect Economic Growth? Evidence from Landsat Data in China

:Employing Landsat data, quantitative indicators relating to urban spatial structure in China—including an urban compactness ratio and an urban elongation ratio—from 2007 to 2016 were selected and quantified. The panel data model indicated that urban compactness was negatively correlated with the urban GDP. Urban elongation was positively correlated with the urban GDP. But the urban elongation and the consumption of land resources cannot sustain urban economic growth in the long run. Therefore, to give full play to the economic benefits of spatial agglomeration and to curb the extensive elongation of urban spatial structure, there is an urgent need to reform the current urbanization mode and employ a market mechanism, changing the single government-regulated mode into a multi-subject cooperative mode.

Impact of high-speed rail on urban economic development: An observation from the Beijing-Guangzhou line based on night-time light images

The high-speed rail (HSR) of China has developed and expanded rapidly and made great achievements in the past twenty years. The ongoing HSR plan is expected to have a significant impact on the urban economy and spatial structure in China. However, relevant data-driven research is still lacking. Traditional data collection approaches such as field surveys are costly to assure the accuracy of materials. In this study, a new remote sensing perspective of night-time light (NTL) was adopted to observe the long-term impact of the HSR on cities along the rail. More specifically, we investigated the impact of the Beijing–Guangzhou High-Speed Railway (BGHSR) on urban economic development by using night-time light data from 2002 to 2018. Such a line connects the capital (located in the north of China) and southern China and lies on the most important geographic axis of the country. Our results find that the construction of BGHSR line has a considerable positive impact on economies of first-tier cities (e.g., Beijing and Guangzhou) and new-first-tier cities (e.g., Zhengzhou, Wuhan, and Changsha), but also hurt some second-tier and third-tier cities such as Baoding and Handan. Generally, the spatial economic pattern of cities along the BGHSR line has been rapidly reshaped with the change of the transportation system. Each city needs to reconsider its role and value in the coming regionalization process to adapt to the national strategy.

Studying the urban hierarchical pattern and spatial structure of China using a synthesized gravity model

The Gravity Model (GM), one of the most classic models adopted by the domain of social sciences from physics, has been widely used to study the interactions between social identities. Previous research that has used the Gravity Model to study the interactions among cities have mostly used a single variable, such as population or GDP, to represent a city, which does not provide a comprehensive depiction of a city’s influence. This paper develops a Synthesized Gravity Model (SGM) based on the traditional Gravity Model to study the evolution of the hierarchy of the Chinese urban system since the mid-1990s. Under this model, socioeconomic variables are synthesized and are represented by the Influential Factor, while the Function Distance is derived from a Network Analysis that is based on multiple transportation methods. As an improvement on the GM, the SGM is used to accurately establish and represent the nodal structure of China’s urban system, the evolution of its hierarchical structure, and the relationships that exist between the nodal structure and socioeconomic factors. The results based on the SGM indicate that China’s national urban system is characterized by the emergence of urban clusters with stronger inter-city interactions since the 1990s. However, the development among cities within certain urban clusters is not even, although the general pattern indicates a lessening inequality amongst cities. Spatially, while most cities at the top of the hierarchy are located in Eastern China, cities in the center and the west of the country are also gaining higher positions in the hierarchy over time. This paper is dedicated to improving the traditional GM in the applications of urban studies, while the system of Chinese cities is used to validate the SGM.

Polycentric Development and the Role of Urban Polycentric Planning in China’s Mega Cities: An Examination of Beijing’s Metropolitan Area

An emerging polycentric spatial structure in China’s mega cities has been confirmed in the literature, but few studies have addressed the linkage between the change in spatial structure and urban development policies. Using Beijing as a case study, this paper examines the role of urban polycentric planning in the polycentric evolution process from a morphological perspective. We observed that urban polycentric planning significantly promoted the emergence of a polycentric urban form in Beijing’s metropolitan area from 2001 to 2010. Firstly, most of the planned subcenters were identified as real employment subcenters by a relative threshold method in 2001 and 2010 and comprised the majority of the employment subcenters. Secondly, the planned subcenters significantly increased their employment share and influence on employment and population distribution from 2001 to 2010, and their performances referring to these aspects were much better than the unplanned subcenters. Thus, our findings provide evidence that changes in urban spatial structure can be strongly affected by urban development policies, although it is determined by market forces in theory.

Stratified evolution of urban residential spatial structure in China through the transitional period: A case study of five categories of housings in Chengdu

Since the reform and opening up, urban spatial organization in China has changed from a planned economy mode to a market driven economy. From 1978 to 2016, the cities in mainland China have developed five types of housing systems: commercial housing, new Danwei housing, affordable housing, demolition resettlement housing, and self-built housing. The reform of the housing system that was started in the 1990s allowed and led to a rapid growth of the commercial housing market, which also resulted in an obvious suburbanization trend. At the same time, the housing reform policy led to the gradual process of marketing individual Danwei within compound housing systems. The state allowed these properties the right to conduct market transactions. However, some policies from the planned economy period remained in place. The Danweis were allowed to retain right of residence and the original management of the Danwei's courtyard but without any trading rights. Demolition resettlement housing and affordable housing are low cost houses built by the local government for the demolished group and the protected group, respectively. The latter can carry on the market transactions after satisfying certain conditions. Self-build housing mainly refers to the rural collective construction of farmers under the ownership of the housing group. Based on the result of the institutional design and benefit game, the land on which the buildings were to be built was part of the structure of the marketing process. Land acquisition negotiations that ranged from simple to complex and profits that ranged from low to high, showed whether lands were being utilized well or were under-developed. These lands are designated as public lands, farmland, industrial lands, Danwei industry courtyards, farmer's homesteads, and institutional lands and courtyards. This has led to a more stable, multivariate, mosaic mixed hybrid urban residential spatial structure in Chinese mainland cities based on the institutional perspective. At the same time, due to the disadvantaged position of the demolition population in the political and economic environment, the location of demolition resettlement housing and affordable housing are gradually being pushed to the suburbs. It is a distinctly different urban residential spatial structure from the cities in Western countries and countries in transition. This embodies the logic of power operation, capital circulation and accumulation and its dual roles. This structure also reflects the complex feature of cooperation and games between different levels of power and social stratum.

Emerging polycentric megacity in China: An examination of employment subcenters and their influence on population distribution in Beijing

Recent decades have witnessed a drastic shift in the spatial structure of China's large cities, from being monocentric to polycentric; however, the existing literature has not completely identified the transformation process, due to a lack of investigation from employment distribution. By using enterprise registration data from 1996, 2001, and 2010, this paper aims to fill the research gap by examining employment subcenters and their effect on population distribution in Beijing. We found that (1) the number of employment subcenters increased from 6 in 1996 to 11 in 2001, and to 16 in 2010; and (2) the population distribution in 2000 was not significantly affected by the appearance of employment subcenters, while the population distribution in 2010 was significantly and positively impacted by distance to the nearest subcenter. These results justify the trend of Beijing becoming a polycentric city.