Spatial Structure Of Urban Agglomeration Research Articles

The Influence of the Spatial Structure of Urban Agglomeration on the Digital Economy and Its Impact Mechanism: Evidence From China

The urban agglomeration (UA), as the carrier of regional economic transformation, is an important impetus for the development of the digital economy (DE) in the future. Based on the perspective of the spatial structure of UA, this paper first attempts to clarify the theoretical aspects of the influence of the spatial structure on DE, its heterogeneous characteristics, and inner impact mechanism, and then empirically test the corresponding hypotheses by utilizing the data on China’s 18 UAs from 2011 to 2019. Our findings are as follows: (1) The monocentric structure has an inverted “U-shaped” impact on DE, namely, first promotion and then inhibition effects. (2) Heterogeneity analysis reveals that the inverted “U-shaped” relationship between the monocentric structure and DE is not observed in UAs lacking megacities and is insignificant during the early and middle development phases of UAs. However, this non-linear relationship becomes significant in UAs with megacities and UAs in mature and later development stages. (3) More deeply, this study uncovers that innovation serves as a mediating factor in the influence of the monocentric structure on DE. This article not only enriches the existing body of research on UAs and DE but also provides valuable theoretical insights for the development of DE within UAs.

Study on Tourism Spatial Structure of Urban Agglomeration in Central Region Based on Social Network Method

With the passage of time, China’s economic development, people’s life gradually pursue enjoyment, so the development of tourism has gradually become an important pillar of national economic development. According to the urban geographical location of the central region, combined with the existing tourism economic conclusions, this paper studies the urban tourism economic data of the central region by using the method of social network, so as to understand the economic development of tourism in the central region in 2019. Through the research, it can be concluded that the correlation of urban tourism economy in Central China is not high among cities, and the tourism economy of cities is relatively different. The strength and influence of tourism economy of central cities with better tourism economic development are much higher than those without tourism economic strength. The tourism economy of each adjacent city circle is relatively close and develops relatively evenly, which shows that the development of tourism economy is closely related to the tourism economic development of adjacent cities. In the urban agglomeration in the central region, there is a high connection between the tourism economy of the cities in the six urban circles. In addition, it can be seen from the tourism economic network diagram of the urban agglomeration in the central region that among the six sub urban agglomerations, the cities in the sub urban agglomerations are closely related to the tourism economy of the central cities in the sub urban agglomerations, but from the perspective of the overall tourism economy, the tourism economic relations among cities are layered, This paper puts forward some suggestions conducive to the integrated development of urban tourism economy in Central China.

The Economic Spatial Structure Evolution of Urban Agglomeration under the Impact of High-Speed Rail Construction: Is There a Difference between Developed and Developing Regions?

It is foreseeable that the next few decades will be the golden age of high-speed rail (HSR) development, with many new construction plans emerging. The construction of the HSR will inevitably cause an impact on the economic spatial structure of urban agglomeration, but it is still unclear whether the impacts differ between economically developed and developing areas. How and to what extent do such differences exist? Based on the modified gravity model, this paper employs a social network analysis method and selects the Yangtze River Delta and Sichuan-Chongqing (Chuanyu) urban agglomeration as the research area to analyze the differences. The main conclusions are as follows. With the construction of HSR: (1) The network density and the average economic connection of urban agglomerations have shown a trend of gradual increase. (2) The number of core areas in developed regions has gradually increased, but there were no changes in the center of developing regions. (3) In developed regions, the new metropolitan areas are the cities that have benefited the most from the HSR construction. In developing regions, the central city with difficult topography benefits the most. (4) The network structure of developed regions tends to be more balanced. The edge cities in developing regions are getting farther from the center.

Identification of Urban Agglomeration Spatial Range Based on Social and Remote-Sensing Data—For Evaluating Development Level of Urban Agglomeration

The accurate identification of urban agglomeration spatial area is helpful in understanding the internal spatial relationship under urban expansion and in evaluating the development level of urban agglomeration. Previous studies on the identification of spatial areas often ignore the functional distribution and development of urban agglomerations by only using nighttime light data (NTL). In this study, a new method is firstly proposed to identify the accurate spatial area of urban agglomerations by fusing night light data (NTL) and point of interest data (POI); then an object-oriented method is used by this study to identify the spatial area, finally the identification results obtained by different data are verified. The results show that the accuracy identified by NTL data is 82.90% with the Kappa coefficient of 0.6563, the accuracy identified by POI data is 81.90% with the Kappa coefficient of 0.6441, and the accuracy after data fusion is 90.70%, with the Kappa coefficient of 0.8123. The fusion of these two kinds of data has higher accuracy in identifying the spatial area of urban agglomeration, which can play a more important role in evaluating the development level of urban agglomeration; this study proposes a feasible method and path for urban agglomeration spatial area identification, which is not only helpful to optimize the spatial structure of urban agglomeration, but also to formulate the spatial development policy of urban agglomeration.

Using Tencent User Location Data to Modify Night-Time Light Data for Delineating Urban Agglomeration Boundaries

The study of urban agglomeration boundaries is helpful to understand the internal spatial structure of urban agglomeration, evaluate the development level of urban agglomeration, and thus, assist in the formulation of regional planning and policies. However, previous studies often used only static spatial elements to delineate the boundaries of urban agglomerations, ignoring the spatial connections within urban agglomerations. In this study, night-time light and Tencent user location data were evaluated separately and fused to delineate urban agglomeration boundaries from both static and dynamic spatial perspectives. Additionally, it has been shown in the study results that the accuracy of urban agglomeration boundary delineated by night-time light data is 84.90%, with Kappa coefficient as 0.6348. The accuracy delineated by Tencent user location data is 82.40%, with Kappa coefficient as 0.5637, while the accuracy delineated by data fusion is 92.70%, with Kappa coefficient as 0.7817. Therefore, it can be concluded that the fusion of night-time light and Tencent user location data had the highest accuracy in delineating urban agglomeration boundaries, which verified that the fusion of dynamic spatial elements on a single static spatial element can supplement the spatial connection of urban agglomeration. Our findings enrich the understanding of urban agglomerations, and the accurate delineation of urban agglomerations boundaries can aid urban agglomeration planning and management.

Spatial structure and carbon emission of urban agglomerations: Spatiotemporal characteristics and driving forces

This paper explores the impact of UASS on carbon emissions. Population and economic factor are taken into the measurement of UASS. GTWR model is to analyze the spatial and temporal differences. BTH, YRD, CP and MRYR show the characteristics of multi-center structure in 2019. PGDP and EI have positive impacts on carbon emissions in all urban agglomerations. To highlight the impact mechanism of spatial structure on carbon emission, this study calculates the spatial structure index of six urban agglomerations in China from the perspective of population and economy by using the rank-size rule. The Geographically and Temporally Weighted Regression (GTWR) model is used to analyze the spatial and temporal differences of the impact of spatial structure on carbon emissions in different urban agglomerations. The research results reveal that the carbon emissions of Yangtze River Delta (YRD), Beijing-Tianjin-Hebei (BTH) and Central Plains (CP) are much higher than that of the other three urban agglomerations. Chengdu-Chongqing (CY) and Pearl River Delta (PRD) show the characteristics of single-center structure, while the other four urban agglomerations show the characteristics of multi-center structure in 2019. The impact of spatial structures on carbon emissions of Yangtze River Delta and Pearl River Delta have experienced the process from positive impact to negative impact. The findings show that the multi-center structure of some urban agglomerations does not achieve the effect of carbon emission reduction to a certain extent, but promotes carbon emission. Therefore, it is not advisable to set the spatial structure of urban agglomeration as a unified model. The government should optimize the spatial structure of urban agglomerations according to the time evolution and internal characteristics of urban agglomerations.

Towards balanced development stage: Regulating the spatial pattern of agglomeration with collaborative optimal allocation of urban land

Urban agglomeration is an important carrier that promotes urbanization into an advanced stage, addressing its unbalanced development is an important task for the newly established territorial spatial planning in China. This research proposed a collaborative optimal allocation of urban land (COAUL) model which provides a simulation tool both for the quantity and spatial structure optimization of urban agglomeration. COAUL first optimizes the quantity structures of every city according to the current situation, potential development capacity and spatial policy. And then the optimized quantity structure is assigned into geo-space with land use spatial optimization model. COAUL has been applied to Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a fast-developing urban agglomeration located in Southern China, and three main findings are obtained: (1) COAUL model can optimize the quantity and spatial structure of urban agglomeration for the goal of balanced development, which could provide scientific reference scenario for the delimitation of the urban agglomerations growth boundaries (UAGB). (2) As cities in urban agglomeration have strong connections with each other, collaborative optimal allocation of urban land could considerably relieve the pressures of developed central cities and also promote the growth of undeveloped edge cities. (3) COAUL can unlimitedly reduce the imbalanced development tendency of urban agglomeration, which is performance better than traditional land use planning models. This research demonstrated that delimiting the UAGB with COAUL model is an important government measure for promoting the balanced development of urban agglomeration areas.

Analysis of socio-economic spatial structure of urban agglomeration in China based on spatial gradient and clustering

Research background: Previous studies on the economic and social development of urban agglomerations mostly focus on a single primacy comparative analysis and efficiency evaluation. Spatial structure differentiation is an important feature of urban agglomeration. The lack of economic and social analysis on the spatial structure makes it impossible to determine the development positioning of each city in the urban agglomeration, which affects the sustainable economic devel-opment ability of these areas.
 Purpose of the article: The objective of the article is to analyze the spatial development law and experience of urban agglomeration, this study explores the practice of economic and population spatial structure of city areas in China. For this purpose, CPUA and its central city Zhengzhou was taken as an example, the spatial gradient structure of example was analyzed.
 Methods: Using economic and population data of 32 cities in this region, growth pole theory, and pole-axis theory, the economic and population spatial structure of urban agglomeration, the spatial gradient structure of central cities in urban agglomerations were analyzed with the method of cluster about radiation index.
 Findings & value added: (1) In the process of the formation of CPUA, the geo-graphical spatial pattern plays a decisive role in economic and social development. This is an experience from developing countries. (2) CPUA presents a gradient development pattern with Zhengzhou as the center, and economic and social development gradually radiates to the metropolitan area, the core development area, and the character development demonstration area. (3) The economic and social gradients of Zhengzhou, the central city, present the hierarchy rules and characteristics which are driven by the Beijing-Guangzhou-Railway axis and the Longhai-Railway axis. (4) The central city of Zhengzhou still presents insufficient primacy in regional development, which shows that Zhengzhou accounts for 6% of the population of the Central Plains Economic Zone and 14% of GDP, and insufficient agglomeration. Different countries at different stages of economic development have different urban agglomeration development models. The conclusions from China provide new decision-making ideas and methods for spatial structure research and development strategy analysis of urban agglomerations.

Understanding the City-transport System of Urban Agglomeration through Improved Space Syntax Analysis

From the perspective of city-transport system, this article applies space syntax to analyze the physical integration of cities. Traditionally, space syntax is mainly applied to urban areas, buildings, and other scales. However, when space syntax is applied to the configuration analysis of urban agglomeration, the change of scale causes changes in spatial perception and human behavioral patterns. Thus, we present a new method of space syntax. This method defines the lane and track between entrance and exit, and city as node, which represents small-scale space. Infrastructure, such as stations, entrances, and exits, are defined as links. The urban agglomeration is thus transformed into a topological network, and then displayed as a bipartite graph of cities and routes. We take the urban agglomerations in the Yangtze River Middle Reaches (YRMR) as the case study area and analyze its spatial configuration from the perspectives of local and integral, interfaces at different scales, gaps, evolution of the dual foreground and background networks, and evolution of the transport networks. The results reveal the way cities integrate with each other and further reveal the multi-scale spatial structure of urban agglomeration.

Analysing the spatial structure of urban growth across the Yangtze River Middle reaches urban agglomeration in China using NPP-VIIRS night-time lights data

The spatial structure of urban agglomeration reveals the self-organization process of internal factors from the outside. As China ushers into a critical stage with the boosting of urbanization and the booming of the economy, measuring the spatial structure of urban agglomerations is vital to urban planning, regional development, etc. Nighttime stable light data from the National Polar–Orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) night-time light (NTL) series dataset offers a novel source that potentially simulates spatial variations in socio-economic activities. The present study aimed to scientifically guide wide applications of the NPP-VIIRS data to define and measure the evolution of urban agglomeration from a spatial–temporal perspective. Yangtze River Middle Reaches (YRMR) Urban Agglomeration (UA) in Central China was taken as the case study region to systematically identify and measure its spatial configuration of urban growth. The light index model and the method of the rank clock were performed to quantify the dynamics of rank-order distributions. In the meantime, spatial statistics and location coefficient index were used to identify the nature and heterogeneity of spatial structure. According to our findings, NPP-VIIRS data can offer insights into the applications to analyze urbanization processes and reveal the dynamics of urban expansion. The proposed framework will help understand the nature and unbalance of spatial configurations of urban economic growth within urban agglomeration and lay a theoretical basis for the policy-making of regional spatial planning.

Impact of spatial structure of urban agglomeration on carbon emissions: An analysis of the Shandong Peninsula, China

Given that carbon emissions continue to contribute to global warming, strategies to achieve reductions in emissions have become a focus for research. The study of the impact of spatial structure of urban agglomeration on carbon emissions has important significance with respect to exploring ways to reduce carbon emissions. The urban agglomeration in the Shandong Peninsula, China was selected as a case study. The spatial structure of urban agglomeration was measured from the perspectives of single-center and multi-center, concentration and diffusion, spatial compactness, and transportation accessibility. Carbon emissions were measured using the standard energy conversion coefficient for coal as well as via coefficients for alternative energy sources. The impact of the spatial structure of urban agglomeration on carbon emissions was assessed via regression analysis. The results revealed that: (1) The impact of multi-center characteristics on carbon emissions was not significant and should be verified using more samples; (2) Concentration and transportation accessibility exerted a positive impact on carbon emissions, therefore, the mode of urban-rural integration and low carbon transportation systems must be taken into account; (3) Spatial compactness exerted a negative impact on carbon emissions, therefore, the patterns of compactness need to be adjusted and optimized.

The Impact of Spatial Structure on Economic Efficiency of Beijing-Tianjin-Hebei Megalopolis in China

This study constructs a theoretical model and empirical framework concerning how spatial structure affects economic efficiency using data on the Beijing-Tianjin-Hebei (BTH) megaregion between 2008 and 2017. The study finds the following: ① the development of the internal spatial structure of the BTH urban agglomeration is unequal. The populations of most cities in the urban agglomeration are still in a dispersed state. Although urban populations have tended to agglomerate around multiple subcenter units in the cities, the trend towards population agglomeration around city centers is not found to be significant. ② The total factor productivity (TFP) of the BTH urban agglomeration was not high in most years between 2008 and 2017, showing a fluctuating downward trend overall. The TFP of the urban agglomeration showed differential regional patterns. The decline of TFP growth in the BTH urban agglomeration is mainly due to declining technological progress, technological efficiency, and scale efficiency. Resource input remains the major driving force behind the development of the BTH megaregion. ③ Concerning how the spatial structure of the urban agglomeration affected economic efficiency, the study finds that primacy, urban Gini index, urban population size, human capital, informatization level, industrial structure, and science and technology levels have positive effects on economic efficiency, whereas dispersion, governmental role, economic openness, and land input have negative effects. This study has several policy implications. Achieving coordinated and integrated development of the BTH urban agglomeration will require constructing a scientific and regional spatial system, improving the development levels of regional central cities, divesting Beijing of noncapital functions, and reshaping the industrial layout of the BTH megaregion in an orderly manner, while continuously improving the internal hierarchical structure of urban agglomeration and strengthening intercity economic connections.

Optimizing the spatial structure of urban agglomeration: based on social network analysis

The development of urban agglomerations is fundamentally influenced by their spatial structure. Based on the case of Beijing–Tianjin–Hebei (BTH) urban agglomeration, this study aims to evaluate the spatial connection intensity and spatial structure characteristics of BTH urban agglomeration and provide tenable suggestions to optimize the BTH urban agglomeration. The TOPSIS model, the revised gravity model, and social network analysis are employed respectively. The findings indicate that: (1) Wide discrepancy exists within the agglomeration in terms of spatial connection intensity. Cities in the central regions have the greatest connection intensity with other cities and then the connection intensity decreases from the middle to the northern and southern parts of the agglomeration. The connection intensity between core cities such as Beijing, Tianjin and Shijiazhuang and the other non-core cities is much lower than the connection intensity among core cities. (2) The social network of BTH urban agglomeration is relatively low-dense and unstable. The centrality degrees of Beijing and Tianjin are the highest, making them the core of the spatial structure of the agglomeration. (3) The BTH urban agglomeration can be divided as three circle layers and four cohesive subgroups, among which Shijiazhuang and Hengshui are two cities dissociating from other cities. Given this, it is urgent that the government should disengage Beijing from its non-capital functions, promote Tangshan and Baoding as bridge cities, so as to enhance the connection intensity between core cities and edge cities, turn Shijiazhuang into the third growth pole other than Beijing and Tianjin, and eventually revolutionize the monopolar structure into a multipolar one.

Spatial structure of urban agglomeration under the impact of high-speed railway construction: Based on the social network analysis

As a typical mode of modern transportation, high-speed rail (HSR) plays a key role in the formation and development of today's regional spatial pattern. Based on the panel data of 2009, 2012, 2015 and 2018, Beijing-Tianjin-Hebei Urban Agglomeration is taken as the research object and the social network analysis method is used by this research to explore the evolution of urban agglomeration spatial structure under the impact of HSR construction. The results show that: Firstly, HSR construction increases the average network density of urban agglomeration by 0.0487, which promotes the spatial connection density of urban agglomeration in a positive way. Secondly, HSR can improve the point centrality of moderately developed cities by 0.87, reduce the spatial connection of urban agglomeration’ dependence on core cities, and improve the urban agglomeration’ stability of spatial structure. Thirdly, HSR can make more cities enter the core subgroup faster, and improve the speed of urban agglomeration evolution to the optimized state. Based on this, the following suggestions are put forward: first, cities without HSR should strengthen urban construction in order to achieve interconnection with cities with HSR as soon as possible. Second, HSR construction should be taken as an opportunity to cultivate new regional hub cities. Third, the transportation planning department should strive to improve the HSR construction level of the peripheral cities so that they can share the effect of HSR construction.

Tourism spatial structure of urban agglomeration in the middle reaches of the Yangtze River based on social network analysis

Based on a revised gravity model, this paper establishes an evaluating indicator and model of the spatial structure of tourism economic linkages in urban agglomeration by using social network theory and method. Tourism spatial economic data of 56 urban in the urban agglomeration of the middle reaches of the Yangtze River were collected. With the help of Ucinet software, we discuss the tourism spatial structure features in the urban agglomeration of the middle reaches of the Yangtze River, and the tourism spatial structure of urban agglomerationis optimized by network density, centrality degree, structural holes, core-periphery structure and condensing subgroup model.

Scenario Modeling of Urbanization Development and Water Scarcity Based on System Dynamics: A Case Study of Beijing-Tianjin-Hebei Urban Agglomeration, China.

Due to the accelerated process of urbanization in China, urban agglomerations have become the core areas for human settlement and economic development. High population and economic density has brought great pressure on water supply. Water scarcity is increasingly becoming one of the most important issues for the sustainable and healthy development of China’s urban agglomerations. In this paper, a system dynamics model was constructed to simulate the current conditions and future scenarios of urbanization development and water scarcity in the Beijing–Tianjin–Hebei (BTH) urban agglomeration in 2000–2030, by examining the interaction and feedback between the six major subsystems: water supply, water demand, water pollution, population urbanization, economic urbanization, and land urbanization. It is found that the South-to-North Water Diversion Project and the improved Reclaimed Water Reuse System may greatly increase the water supply. However, the speed of population urbanization and economic growth, the spatial structure of urban agglomeration and the water consumption pattern may determine the water demand. Although all scenarios may risk water scarcity in the future at some point, we could detect a comprehensive and relatively rational scenario to balance water scarcity, regional equity, and efficiency. It might help to synthetically understand the coordinated development mode between urbanization and water resources in Beijing–Tianjin–Hebei (BTH) urban agglomeration, and provide a useful analytical and decision support tool for scientists and policy-makers to achieve the sustainable urbanization development and water resource management.

Количественный анализ многозональных космических изображений городских агломераций. Часть 1

В статье на основе экспериментальных исследований показана возможность использования современных методов автоматизированной обработки многозональных космиче­ских изображений для изучения пространственной структуры городских агломераций и оценки состояния составляющих урболандшафта. В первой части статьи приводятся резуль­таты использования классификационного и линеаментного анализа. Показана полезность использования данных видов анализа для количественной оценки составляющих урболандшафта и пространственной структуры городской агломерации. Во второй части статьи приводятся результаты использования мультифрактального анализа и метода диа­грамм «энтропия - сложность» для количественного описа­ния пространственной организации и степени структурной вариабельности городских агломераций по их космическим изображениям. Рассчитанные мультифрактальные спектры демонстрируют изменчивость мультифрактальных характе­ристик для различных городских агломераций мегаполиса Ханой, указывающую на неоднородность пространственной структуры мегаполиса, которая может быть параметризована с помощью мультифрактальных спектров.
 Перспективность использования количественного анали­за космических изображений заключается в том, что на его основе можно выполнить анализ и оценку пространственной структуры городской агломерации в целом и входящих в её границы городских поселений с опорой на количественные критерии, определяемые дистанционными методами.

The Method and Application of Graphic Recognition of the Social Network Structure of Urban Agglomeration

The spatial structure of urban agglomeration is an important branch of economic geography. As far as the current scholars’ research is concerned, the research method of urban agglomeration is relatively simple, and the visual effect of the results is poor. In this paper, the theory of social network analysis is used and the relationship within the urban agglomeration is expressed by using the UCINET6.0 and NETDRAW software. And then, the Urban Agglomeration along the middle reaches of the Yangtze River is taking as the object of empirical research. The Urban Agglomeration along the middle reaches of the Yangtze River, one of the most intensive areas of education in China, undertakes the important mission of building a new growth pole in China. However, the phenomenon of “group instead of cluster” has always been the bottleneck of besetting healthy development of the urban agglomeration, and the cluster effect appears a decreasing trend. This paper uses the modified economic gravity model and social network analysis method and constructs the “three-dimensional” diagnosis model of social network structure of urban agglomeration consisted of the primate city—social network structure density—social network structure intensity. The economic membership grade and centricity of the primate city, social network structure density of the urban agglomeration and coherent subgroup, and the social network structure intensity of the Urban Agglomeration in the middle reaches of the Yangtze River is measured. It demonstrates the spatial structure of the Urban Agglomeration along the middle reaches of the Yangtze River shows the social network structure characteristics of “weak center traction and discrete clusters”, and points out three problems restricting the Urban Agglomeration along the middle reaches of the Yangtze River. With the introduction of new theories, a three-dimensional diagnostic tool of social network structure of urban agglomerations is designed, which provides theoretical support and decision support for solving the problem of “group instead of cluster” in urban agglomeration.

Spatial structure evolution of Changsha-Zhuzhou-Xiangtan urban agglomeration

Conditions and stages of spatial structure’s evolution in the region of Changsha-Zhuzhou-Xiangtan were analyzed. Evolutionary rules and features of Changsha-Zhuzhou-Xiangtan urban agglomeration were summarized through the regional spatial structure composed of 6 elements: node, channel, network, domain surface, grade and flow. Urban agglomeration in traditional agricultural economy era has features of low-level discrete spatial structure such as: inadequate contact and interaction among cities, imperfect channels, indistinct hierarchical structure, inadequate network, and low level of mobility; spatial structure of urban agglomeration during the planned economy era is under the top–to-down control in a rationally planned status of balance, which is a kind of planned space; economic space during the transitional economy era is a kind of space with non-balance and increasing polarization. The industrial structure rapidly transforms and upgrades. The function of spatial organization is becoming increasingly important, different kinds of spatial channels are rapidly constructed and become perfect. The hierarchical structure becomes more and more complicated with rapid increase of mobility. The Changsha-Zhuzhou-Xiangtan urban agglomeration in the future will enter the age of being informationized, ecological and being systematic in space and integrated between urban and rural areas.

Stability of spatial structure of urban agglomeration in China based on Central Place Theory

This paper brings forward the concept of stability of the spatial structure of urban agglomeration (UA) based on Central Place Theory by introducing centrality index and fractal theory. Before assessment, K=4 is selected as parameter to calculate centrality index and fractal dimension (K represents the quantitive relationship between city and the counties in Central Place Theory), and then found the number of nodes, the type of spatial structure, the spatial allocation of nodes with different hierarchy affecting the stability of spatial structure. According to spatial contact direction and the level of stability, UAs in China are classified into five types. Finally, it is posed as a further question that how to use hierarchical relation K=6 and K=7 in central place system to coordinate with the assessment of stability of spatial structure is brought forward.