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Spatial Pattern and Evolution of Urban System Based on Gravity Model and Whole Network Analysis in the Huaihe River Basin of China

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Spatial Pattern and Evolution of Urban System Based on Gravity Model and Whole Network Analysis in the Huaihe River Basin of China Hindawi Discrete Dynamics in Nature and Society Volume 2018, Article ID 3698071, 11 pages https://doi.org/10.1155/2018/3698071 Research Article Spatial Pattern and Evolution of Urban System Based on Gravity Model and Whole Network Analysis in the Huaihe River Basin of China Yong Fan ,1,2 Shengdi Zhang,3 Zongyi He ,4 Biao He ,1 Haicong Yu,5 Xiaoxiao Ye,4 Hao Yang,4 Xiangmin Zhang,2 and Zhifeng Chi2 1 Research Institute for Smart Cities and Shenzhen Key Laboratory of Spatial Information Smart Sensing and Services, School of Architecture and Urban Planning, Shenzhen University, Shenzhen, China 2College of Geographic Sciences, Xinyang Normal University, Xinyang, China 3Garmin, Shanghai, China 4School of Resource and Environmental Sciences, Wuhan University, Wuhan, China 5Center for Assessment and Development of Real Estate, Shenzhen, China Correspondence should be addressed to Biao He; whu [email protected] Received 14 January 2018; Revised 9 May 2018; Accepted 28 May 2018; Published 27 June 2018 Academic Editor: Leonid Shaikhet Copyright © 2018 Yong Fan et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Te spatial pattern and evolution of urban system have been hot research issues in the feld of urban research. In this paper, the network analysis method based on the gravity model and the related measurements were used to reveal the properties of the spatial pattern and evolution of the urban system in the HRB (Huaihe River Basin) of China. Te fndings of this study are as follows: During the period from 2006 to 2014, the economic contact between the HRB cities has been strengthened, but the diferences between cities have been expanding. In general, the HRB cities have not yet formed a close network structure, and a trend of economic integration has not been found. Tis paper expresses the spatial pattern and evolution of urban system in an intuitive way and helps to explain the evolution mechanism of urban system. Te method was confrmed by empirical research. Because of the operational and visual expression, this method has broad application prospects in the urban system research. 1. Introduction Fuzhou-Xiamen, Harbin-Daqing-Qiqihar, and Wuhan area [3, 4]. If the geographical positions of urban agglomera- Te spatial pattern and evolution of urban system are impor- tions are compared with several main rivers in China (the tant manifestations of the human social development process Changjiang River, the Huanghe River, the Liaohe River, on a spatial level [1], which refects the change in the human the Huaihe River, the Songhuajiang River, the Pearl River, socialspatialstructureandrevealsthespatialpatternsof the Haihe River, and the Minjiang River), it can be found the overall behavior of human society. Tese changes and that they mostly have corresponding relations. Only the their patterns are the foundations for the research of the HRB (Huaihe River Basin) has not formed large scale sustainable development of human society [2]. urban agglomeration [5]. Terefore, this paper wishes to Six super-large urban agglomerations have been formed determine the relationship between the HRB cities and puts in mainland China: Shanghai-Nanjing-Hangzhou, Beijing- forwardfeasiblesuggestionstopromotecontactbetween Tianjin-Tangshan, Pearl River Delta, the central and southern cities [6]. Liaoning Province, Sichuan Basin, and Shandong Penin- Population and economic growth are the main driving sula. Six city-and-town-concentrated areas (approximate forces for the growth of urban system [7]. Te cellular tourbanagglomeration)havealsobeenformed:Central automata model [8], support vector machine [9], self- Shanxi Province, Central Hunan Province, Central Plains, organizing structure model [10], gravity model [11], and 2 Discrete Dynamics in Nature and Society systematic dynamics [12] have been used to describe spatial which describes the interaction between the two masses expansion of cities. Te growth of urban systems is also M1 and M2 of objects, where d is the distance between the infuenced by the scale of urban space, trafc network, and two objects and G is the universal gravitation constant. complexity of the terrain [13–15]. A mechanism for the Similar to the interaction between objects, there is also growth of the city has been proposed [16] but modeling a relationship between cities in a certain area; in economics, the spatial and temporal dynamics of urban formation and this is called economic gravity theory [33, 34]. evolution remains difcult [17]. Urban systems evolution Because of this similarity, many scholars have attempted mainly includes changes in two aspects: land use pattern to apply the formula of universal gravitation to the measure- and system structure [18]. Te gravity model has been ment of a city’s gravity: widely applied in this feld. Based on graph theory, large �1 �2 G� � scale analysis has demonstrated that the spatial structure of � = � � , �� �3 (2) urban system becomes increasingly efective and stable with ��� increased complexity and more favorable to the sustainable � � development of the urban system [19]. where �� denotes the quantity of spatial fows. � and �� aretheGDP(GrossDomesticProduct)ofacity;� is the Te formation of urban agglomeration is not only con- 1 2 3 nected with geographical location and distribution of the city distance between two cities; �, � , � , � are constants. but also relevant to the economy and social culture [20]; To describe the scale and development degree of a city the cross-border movement of capital, information, products, more scientifcally, some scholars have also considered the talented people, and technology is the notable feature of population and area of a city when constructing the model regional economic development [21, 22]. [35, 36]. From previous literature, we know that network analysis However,citiesarenotthesameasordinaryobjects.Te canbeusedtoanalyzeresourceexchangeandrelation economic impact of city i on city j is not equal to the economic between actors (i.e., individuals, groups, cities, etc.) [23]. impact of city j on city i,andthecontributionsofthetwocities Because of this characteristic, network analysis has a great to the economic gravity are also diferent. Consequently, we contribution in the feld of information exchange [24], defned the constant as the ratio of GDP in city i to the GDP group behavior research, and other felds [25, 26]. However, in city i and city j, and the modifed gravity model is thus although network analysis has received great concern in obtained: regional economics since the last century [27], only in recent √���� × √���� years whole network analysis has been used to study regional � =� economic network structures [28–30]. Te method of whole �� �� 2 ��� network analysis could be used to study the relationship, (3) especially economic contact, among cities. �� ��� = , Currently, the main focus of whole network urban system �� +�� is on explicit urban networks (i.e., trafc networks [14, 19]) � � or the ranking of urban system centers, but there is a lack where � and � are the registered population in city i 2 of dynamic and visual expression on internal membership and city j; �� and �� are the GDP in city i and city j; ��� is in urban system [31]. Te distinction between an urban the distance between city i and city j; ��� is the contribution system, as a specifc geographical cluster, and a city is rate from city i to city j.Ifthecityisataprefecturelevelor its complex interactions and connections among network above, the statistical data do not include the counties under members. Terefore, the internal connection of urban system thejurisdictionofthatcity. should be multilateral, interactive, and networked [32]. First, We calculated the ��� of all the cities in the HRB Tese studies provide a method foundation for under- basedon(3)andshowedtheresultasamatrix.Ten,urban standing the urban systems evolution. Our goal was to explain system network structure of the HRB was calculated and the urban system structure based on temporal and spatial analyzed using Ucinet Platform. evolution and use this to reconstruct the timelines of spatial patterns of regional urban system. Accordingly, in this paper, 2.2. Whole Network Analysis a modifed gravity model is used to construct the network with the location, scale, and economic level data of the HRB 2.2.1. Density. Network Density refers to the closeness degree cities,andthemethodofwholenetworkanalysisisused among the network members: the closer the members, the to study the urban network structure and the relationships higher the density of the network. For a binary network, among cities. its density is the ratio of the number of actual relationships in the network to the theoretical maximum number of 2. Theories and Methods relationships, whereas for a multivalued network, such as the network analyzed in this paper, its density is the average of all 2.1. Gravity Model. Te gravity model is based on the formula contact values except self-contact: of universal gravitation: ��� G�1�2 �=∑ ∑ , �= , (1) (�2 −2�) (4) �2 � �,�=�̸ Discrete Dynamics in Nature and Society 3 where ��� istheeconomicimpactofcityi on city j; n is the Centralization is used to describe the overall centrality number of cities in the urban network. of a network; namely, it compares the highest degree of centrality in the network with the other members’ central- 2.2.2. Degree
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