Journal of Geographical Sciences >
Analysis of city centrality based on entropy weight TOPSIS and population mobility: A case study of cities in the Yangtze River Economic Belt
Luo Jing (1966), Professor, specialized in human geography and economic geography. Email: luojing@mail.ccnu.edu.cn 
Received date: 20190425
Accepted date: 20191229
Online published: 20200625
Supported by
National Natural Science Foundation of China(41871176)
The “Hua Bo” Plan of Central China Normal University
Postgraduate Education Innovation Subsidy Project of Central China Normal University(2018CXZZ004)
Copyright
Based on statistical data and population flow data for 2016, and using entropy weight TOPSIS and the obstacle degree model, the centrality of cities in the Yangtze River Economic Belt (YREB) together with the factors influencing centrality were measured. In addition, data for the population flow were used to analyze the relationships between cities and to verify centrality. The results showed that: (1) The pattern of centrality conforms closely to the poleaxis theory and the central geography theory. Two axes, corresponding to the Yangtze River and the ShanghaiKunming railway line, interconnect cities of different classes. On the whole, the downstream cities have higher centrality, welldefined gradients and better development of city infrastructure compared with cities in the middle and upper reaches. (2) The economic scale and size of the population play a fundamental role in the centrality of cities, and other factors reflect differences due to different city classes. For most of the coastal cities or the capital cities in the central and western regions, factors that require longterm development such as industrial facilities, consumption, research and education provide the main competitive advantages. For cities that are lagging behind in development, transportation facilities, construction of infrastructure and fixed asset investment have become the main methods to achieve development and enhance competitiveness. (3) The mobility of city populations has a significant correlation with the centrality score, the correlation coefficients for the relationships between population mobility and centrality are all greater than 0.86 (P<0.01). The population flow is mainly between highclass cities, or highclass and lowclass cities, reflecting the high centrality and huge radiating effects of highclass cities. Furthermore, the cities in the YREB are closely linked to Guangdong and Beijing, reflecting the dominant economic status of Guangdong with its geographical proximity to the YREB and Beijing’s enormous influence as the national political and cultural center, respectively.
LUO Jing , CHEN Siyun , SUN Xuan , ZHU Yuanyuan , ZENG Juxin , CHEN Guangping . Analysis of city centrality based on entropy weight TOPSIS and population mobility: A case study of cities in the Yangtze River Economic Belt[J]. Journal of Geographical Sciences, 2020 , 30(4) : 515 534 . DOI: 10.1007/s1144202017409
Figure 1 Location and administrative divisions of the Yangtze River Economic Belt 
Table 1 Symbol of each indicator 
Indicator  Symbol  Indicator  Symbol 

Total permanent residential population  C1  Number of authorized patents  C10 
GDP  C2  Hightech output value  C11 
Added value of secondary and tertiary industries  C3  Number of highspeed railway and express railway stations  C12 
Total fixed assets investment  C4  Number of civil airports  C13 
Total retail sales of consumer goods  C5  Total amount of cargo transported  C14 
Actual use of foreign investment  C6  Total number of passengers transported  C15 
Amount of imports and exports  C7  Number of colleges and universities  C16 
Tourism income  C8  Number of students in colleges and universities  C17 
R&D expenditure  C9 
Table 2 Data sources for indicators 
Indicators  Data sources 

C1, C2, C3, C4, C5, C6, C14, C15, C16, C17  China Urban Statistical Yearbook (2017) 
C1, C2, C3, C4, C5, C6, C7, C8, C9, C10, C11, C14, C15, C16, C17  Statistical Yearbooks (2017) of the cities in the YREB 
C1, C2, C3, C4, C5, C6, C7, C8, C9, C10, C11, C14, C15, C16, C17  2016 National Economic and Social Development Statistics Bulletin of the cities in the YREB 
C12  12306 China Railway (https://www.12306.cn/mormhweb/czyd_2143/) 
C13  2016 Civil Aviation Airport Production Statistics Bulletin of China (http://www.caac.gov.cn/XXGK/XXGK/TJSJ/201702/t20170224_42760.html) 
Note: The above data are for 2016. The 2017 Statistical Yearbooks contain data for 2016. 
Table 3 Weight of each indicator 
Indicator  Weight  Indicator  Weight 

C1  0.0691  C10  0.0572 
C2  0.1039  C11  0.0708 
C3  0.0781  C12  0.0480 
C4  0.0581  C13  0.0403 
C5  0.0659  C14  0.0408 
C6  0.0654  C15  0.0423 
C7  0.0514  C16  0.0527 
C8  0.0363  C17  0.0616 
C9  0.0581  —  — 
Figure 2 Scores and classes of city centrality in the Yangtze River Economic Belt 
Figure 3 Clustering of city centrality of the Yangtze River Economic Belt 
Figure 4 Hotspot analysis of city centrality of the Yangtze River Economic Belt 
Figure 5 The top 5 factors influencing city centrality in the Yangtze River Economic Belt 
Figure 6 Ranking of cumulative contributions of the top 5 indicators in the ranking of cities of different classes in the Yangtze River Economic Belt 
Table 4 The correlation coefficient between population flows and the centrality scores of cities in the Yangtze River Economic Belt 
Classification  Correlation coefficient  P 

The correlation coefficient between population inflows and the centrality scores of cities in the YREB  0.9030  8.56E49 
The correlation coefficient between population outflows and the centrality scores of cities in the YREB  0.9257  6.66E56 
The correlation coefficient between population entering the YREB from other cities in China and the centrality scores of cities in the YREB  0.9508  5.48E67 
The correlation coefficient between population flowing out of the YREB to other cities in China and the centrality scores of cities in the YREB  0.8613  1.84E39 
Figure 7 Population inflows between cities in the Yangtze River Economic Belt (The above data are for 2016) 
Table 5 The source city for population inflow from different classes of city in the Yangtze River Economic Belt 
The source city for population inflow from firstclass cities  The source city for population inflow from secondclass cities  The source city for population inflow from thirdclass cities  The source city for population inflow from fourthclass cities  The source city for population inflow for fifthclass cities  

Class  Proportion (%)  Class  Proportion (%)  Class  Proportion (%)  Class  Proportion (%)  Class  Proportion (%) 
First  55.01  First  35.85  Second  43.09  Second  33.81  First  43.15 
Second  23.65  Third  23.43  First  28.25  First  31.06  Fourth  22.34 
Fourth  13.78  Second  19.91  Third  14.86  Fourth  18.83  Second  19.76 
Fifth  4.96  Fourth  17.71  Fourth  12.20  Third  11.58  Fifth  8.38 
Third  2.59  Fifth  3.10  Fifth  1.60  Fifth  4.73  Third  6.38 
The above data are for 2016. 
Figure 8 Population outflows between cities in the Yangtze River Economic Belt (the above data are for 2016) 
Table 6 The destination city for the population outflow from different classes of city in the Yangtze River Economic Belt 
The destination city for the population outflow from firstclass cities  The destination city for the population outflow from secondclass cities  The destination city for the population outflow from thirdclass cities  The destination city for the population outflow from fourthclass cities  The destination city for the population outflow from fifthclass cities  

Class  Proportion (%)  Class  Proportion (%)  Class  Proportion (%)  Class  Proportion (%)  Class  Proportion (%) 
First  42.39  First  42.39  Second  38.11  Second  28.49  First  36.00 
Second  22.47  Second  22.47  First  23.55  First  26.60  Fourth  28.46 
Fourth  21.68  Fourth  21.68  Fourth  18.50  Fourth  25.50  Second  17.40 
Fifth  7.91  Fifth  7.91  Third  17.85  Third  13.27  Fifth  10.48 
Third  5.55  Third  5.55  Fifth  2.00  Fifth  6.15  Third  7.66 
The above data are for 2016. 
Figure 9 The population flows into the Yangtze River Economic Belt from other parts of China (the above data are for 2016) 
Table 7 Source areas (outside the YREB) for population inflow for different classes of city in the Yangtze River Economic Belt 
Source area of the population inflow for firstclass cities  Source area for the population inflow for secondclass cities  Source area for the population inflow for thirdclass cities  Source area for the population inflow for fourthclass cities  Source area for the population inflow for fifthclass cities  

Area Proportion (%)  Area Proportion (%)  Area Proportion (%)  Area Proportion (%)  Area Proportion (%)  
Guangdong  45.32  Beijing  44.73  Guangdong  61.27  Guangdong  59.70  Guangdong  55.08% 
Beijing  34.38  Guangdong  39.68  Beijing  29.68  Beijing  25.77  Beijing  33.12 
Jilin  4.50  Guangxi  4.51  Henan  3.11  Fujian  5.43  Fujian  3.45 
Hainan  4.45  Jilin  3.62  Fujian  1.77  Guangxi  2.63  Henan  2.49 
Shaanxi  3.45  Shandong  2.00  Shandong  1.25  Henan  2.06  Tibet  1.46 
Tianjin  3.06  Henan  1.36  Shaanxi  0.68  Shaanxi  0.98  Hainan  1.43 
Liaoning  1.54  Tianjin  1.21  Heilongjiang  0.38  Hainan  0.93  Guangxi  0.77 
Hong Kong  1.54  Shaanxi  1.12  Guangxi  0.38  Tianjin  0.91  Shandong  0.75 
Fujian  0.79  Hainan  0.87  Liaoning  0.38  Hebei  0.42  Shaanxi  0.59 
Tibet  0.72  Hebei  0.32  Tianjin  0.34  Liaoning  0.41  Tianjin  0.23 
Shandong  0.14  Heilongjiang  0.26  Jilin  0.19  Tibet  0.23  Hebei  0.22 
Inner Mongolia  0.11  Inner Mongolia  0.14  Hainan  0.14  Shandong  0.19  Liaoning  0.14 
—  —  Gansu  0.11  Gansu  0.14  Jilin  0.13  Jilin  0.12 
—  —  Liaoning  0.07  Tibet  0.14  Gansu  0.10  Gansu  0.08 
—  —  —  —  Ningxia  0.10  Shanxi  0.03  Xinjiang  0.04 
—  —  —  —  Hebei  0.04  Heilongjiang  0.03  Shanxi  0.04 
—  —  —  —  Shanxi  0.01  Inner Mongolia  0.03  —  — 
—  —  —  —  Qinghai  0.01  Macao  0.03  —  — 
The above data are for 2016. 
Table 8 Destination areas (outside the YREB) for population outflow for different classes of city in the Yangtze River Economic Belt 
Destination area for the firstclass city outflow population  Destination area for the secondclass city outflow population  Destination area for the thirdclass city outflow population  Destination area for the fourthclass city outflow population  Destination area for the fifthclass city outflow population  

Area proportion (%)  Area proportion (%)  Area proportion (%)  Area proportion (%)  Area proportion (%)  
Guangdong  37.59  Beijing  49.46  Guangdong  43.24  Guangdong  47.26  Guangdong  46.21 
Beijing  37.18  Guangdong  32.44  Beijing  40.21  Beijing  31.46  Beijing  38.21 
Hainan  5.16  Guangxi  3.59  Henan  7.17  Fujian  5.57  Fujian  4.13 
Jilin  3.94  Henan  3.52  Shandong  2.09  Henan  4.89  Henan  4.09 
Tianjin  3.91  Shandong  3.28  Shaanxi  1.22  Guangxi  3.51  Shandong  1.65 
Shaanxi  3.33  Jilin  3.12  Fujian  1.20  Shaanxi  2.17  Tibet  1.61 
Hong Kong  2.33  Shaanxi  1.07  Jilin  0.96  Tianjin  1.39  Hainan  1.13 
Shandong  2.30  Tianjin  0.89  Heilongjiang  0.82  Hainan  1.04  Shaanxi  1.10 
Liaoning  1.79  Fujian  0.79  Guangxi  0.81  Shandong  0.71  Guangxi  0.99 
Tibet  1.48  Hebei  0.49  Liaoning  0.63  Liaoning  0.67  Tianjin  0.49 
Fujian  0.85  Hainan  0.48  Tianjin  0.60  Hebei  0.54  Shanxi  0.18 
Inner Mongolia  0.14  Heilongjiang  0.45  Tibet  0.31  Tibet  0.34  Hebei  0.10 
—  —  Inner Mongolia  0.24  Gansu  0.24  Gansu  0.22  Gansu  0.07 
—  —  Liaoning  0.17  Hebei  0.21  Jilin  0.11  Liaoning  0.04 
—  —  —  —  Hainan  0.19  Inner Mongolia  0.05  Ningxia  0.01 
—  —  —  —  Hong Kong  0.10  Heilongjiang  0.05  —  — 
—  —  —  —  Shanxi  0.01  Macao  0.03  —  — 
—  —  —  —  —  —  Shanxi  0.02  —  — 
The above data are for 2016. 
Figure 10 Population outflow from the Yangtze River Economic Belt to other parts of China (the above data are for 2016) 
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