| Literature DB >> 36078365 |
Yihao Jiang1, Zhaojin Chen1, Pingjun Sun1.
Abstract
In the global trend of urban shrinkage, urban vitality, as one of the important representations of high-quality urban development, has become a breakthrough. More and more scholars advocate to awaken urban vitality, so as to realize the high-quality development of shrinking cities. This paper takes the municipal districts of 34 cities in the three northeastern provinces of China as study areas, based on the broad concept of urban shrinkage, selects the indicators of population, economy and society, and uses the "two-step diagnostic method" which is consistent with Chinese conditions to identify the urban shrinkage from 2010 to 2018. In this research, the indexes of economic, social, cultural, environmental and spatial dimensions are selected, and the urban vitality and the vitality of each dimension from 2010 to 2018 are calculated and analyzed by using the entropy weight method (EWM). Then, this paper analyzes the correlation between urban shrinkage and urban vitality by Pearson correlation coefficient. The results show that: (1) urban shrinkage in the three northeastern provinces of China has become a regional remarkable phenomenon, which is also an inevitable process in some regions of China and even the world; (2) overall, the urban vitality of cities in the three northeastern provinces of China is steady and rising a little, and there is an obvious spatial agglomeration pattern like "central city polarization"; (3) there is a significant correlation between urban shrinkage and urban vitality, that is, the lower the degree of urban shrinkage, the higher the urban vitality, showing the opposite trend in the process of urban development; (4) the influence of urban shrinkage on each dimension of urban vitality is different, and the correlation results are different, too. In the planning process of shrinking cities in the future, paying attention to the relationship between urban vitality and urban shrinkage, conducting benign guidance on this basis, and adjusting urban vitality elements of different dimensions to stimulate urban development power can enhance urban competitiveness and achieve better development.Entities:
Keywords: correlation analysis; shrinking cities; the three northeastern provinces of China; two-step diagnostic method; urban shrinkage; urban vitality
Mesh:
Year: 2022 PMID: 36078365 PMCID: PMC9518137 DOI: 10.3390/ijerph191710650
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Figure 1The theoretical connection between urban shrinkage and urban vitality.
Figure 2Geographical location of the three northeastern provinces of China. Note: The figure number is GS(2019)1822.
Index system of urban shrinkage.
| Object | Demographic Dimension | Economic Dimension | Social Dimension |
|---|---|---|---|
| Index | I1: The annual average population of municipal districts | I2: Gross domestic product (GDP) | I5: Total retail sales of social consumer goods |
| I3: Per capita disposable income | I6: The number of doctors | ||
| I4: The proportion of tertiary industry output value to GDP |
Stages of urban shrinkage and the classification criteria.
| Stage of Urban Shrinkage | Criterions * |
|---|---|
| Non-shrinkage | X1 > 0 |
| Slight shrinkage | −3 ≤ X1 < 0 |
| Preliminary shrinkage | −5 ≤ X1 < −3 and A ≥ −20 |
| Middling shrinkage | −10 ≤ X1 < −5, or X1 < −10 and A > 0, or −5 ≤ X1 < −3 and A ≤ −20 |
| Severe shrinkage | X1 ≤ −10 and A < 0 |
* The criterions in the table are compiled according to the existing research [28,33].
Index system of urban vitality.
| Dimension | Indicator | Explain of the Index | Number of the Index | References |
|---|---|---|---|---|
| Economic vitality | Income level | Per capita disposable income | 1 | [ |
| Residents’ Consumption level | Total retail sales of social consumer goods | 2 | [ | |
| Investment of foreign capital | The actual amount of foreign capital used | 3 | [ | |
| Economic growth | Growth rate of GDP | 4 | [ | |
| Industrial structure | The proportion of tertiary industry output value to GDP | 5 | [ | |
| Market size | The number of enterprises in domestic-funded industries above the scale | 6 | [ | |
| Social vitality | Innovation capacity | The number of annual patent applications per 10,000 people | 7 | [ |
| Unemployment | Percentage of registered unemployed people in cities | 8 | [ | |
| Demographic Changes | Natural population growth rate | 9 | [ | |
| Population density | The number of people per unit area | 10 | [ | |
| Medical insurance | The number of doctors per 10,000 people | 11 | [ | |
| Cultural vitality | Cultural development | The number of books in public libraries per 100 people | 12 | [ |
| cultural consumption | The proportion of employees in education, culture, sports and entertainment | 13 | [ | |
| Environmental vitality | Greening level | Per capita park green space area | 14 | [ |
| Water supplying capacity | Per capita water supply | 15 | [ | |
| Power supplying capacity | Per capita electricity consumption | 16 | [ | |
| Discharging capacity | The density of drainage pipe | 17 | [ | |
| Spatial vitality | Accessibility of traffic | The density of roads in cities | 18 | [ |
| Efficiency of public transportation | The number of buses per 10,000 people | 19 | [ | |
| The level of living space | Area of per capita residential land for construction | 20 | [ |
Identification results of shrinking cities in three northeastern provinces of China.
| City | The Starting Year of Shrinking | The End Year of Shrinking | Population Growth Rate (%) | The First Step of Judgment | The Second Step of Judgment | Stage of Shrinking |
|---|---|---|---|---|---|---|
| Harbin | 0 | No pass | Non-shrinkage | |||
| Qiqihar | 2010 | 2018 | −6.6767 | Pass | −19.7208 | Middling shrinkage |
| Jixi | 2010 | 2018 | −12.9615 | Pass | −3.2914 | Severe shrinkage |
| Hegang | 2010 | 2018 | −11.3279 | Pass | No pass | Middling shrinkage |
| Shuangyashan | 2012 | 2014 | −6.0070 | Pass | −5.5404 | Middling shrinkage |
| 2016 | 2018 | |||||
| Daqing | 2013 | 2018 | 0 | No pass | Non-shrinkage | |
| Yichun | 2012 | 2017 | −7.5342 | Pass | −3.8713 | Middling shrinkage |
| Jiamusi | 2012 | 2017 | −5.5844 | Pass | No pass | Middling shrinkage |
| Qitaihe | −18.9583 | Pass | −10.9921 | Severe shrinkage | ||
| Mudanjiang | 0 | No pass | Non-shrinkage | |||
| Heihe | 2011 | 2017 | 0 | No pass | Non-shrinkage | |
| Suihua | −9.2683 | Pass | −4.0642 | Middling shrinkage | ||
| Changchun | 0 | No pass | Non-shrinkage | |||
| Jilin | 2011 | 2015 | −0.7807 | Pass | No pass | Slight shrinkage |
| Siping | 2011 | 2016 | −4.7806 | Pass | −8.6928 | Preliminary shrinkage |
| Liaoyuan | 0 | No pass | Non-shrinkage | |||
| Tonghua | 2010 | 2013 | −1.9929 | Pass | −11.0414 | Slight shrinkage |
| 2015 | 2018 | |||||
| Baishan | 2011 | 2018 | −12.0755 | Pass | No pass | Middling shrinkage |
| Songyuan | 0 | No pass | Non-shrinkage | |||
| Baicheng | 2012 | 2016 | −3.6735 | Pass | −1.7364 | Preliminary shrinkage |
| Shenyang | 0 | No pass | Non-shrinkage | |||
| Dalian | 0 | No pass | non-shrinkage | |||
| Anshan | 2013 | 2018 | −2.5000 | Pass | −11.0960 | Slight shrinkage |
| Fushun | 2013 | 2018 | −4.8905 | Pass | −6.7867 | Preliminary shrinkage |
| Benxi | 2010 | 2018 | −5.9222 | Pass | −11.0951 | Middling shrinkage |
| Dandong | 2011 | 2016 | −1.0256 | Pass | No pass | Slight shrinkage |
| Jinzhou | 0 | No pass | Non-shrinkage | |||
| Yingkou | 0 | No pass | Non-shrinkage | |||
| Fuxin | 2013 | 2016 | −2.2368 | Pass | −9.4948 | Preliminary shrinkage |
| Liaoyang | 2014 | 2017 | −1.9767 | Pass | −0.9507 | Slight shrinkage |
| Panjin | 0 | No pass | Non-shrinkage | |||
| Tieling | 2011 | 2016 | −3.7209 | Pass | −22.2522 | Middling shrinkage |
Scores and ranks of urban vitality in three northeastern provinces of China.
| City | 2010 | 2011 | 2012 | 2013 | 2014 | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Score | Rank | Score | Rank | Score | Rank | Score | Rank | Score | Rank | |
| Harbin | 0.37 | 4 | 0.50 | 3 | 0.44 | 3 | 0.42 | 4 | 0.51 | 3 |
| Qiqihar | 0.20 | 16 | 0.21 | 17 | 0.25 | 11 | 0.23 | 15 | 0.24 | 15 |
| Jixi | 0.17 | 24 | 0.18 | 22 | 0.19 | 26 | 0.17 | 30 | 0.18 | 24 |
| Hegang | 0.19 | 18 | 0.18 | 20 | 0.22 | 17 | 0.20 | 25 | 0.17 | 29 |
| Shuangyashan | 0.15 | 29 | 0.16 | 26 | 0.21 | 20 | 0.21 | 18 | 0.17 | 27 |
| Daqing | 0.35 | 5 | 0.33 | 5 | 0.37 | 5 | 0.35 | 5 | 0.40 | 5 |
| Yichun | 0.14 | 32 | 0.15 | 30 | 0.19 | 27 | 0.17 | 31 | 0.15 | 30 |
| Jiamusi | 0.18 | 20 | 0.20 | 18 | 0.23 | 15 | 0.21 | 20 | 0.20 | 20 |
| Qitaihe | 0.19 | 17 | 0.14 | 33 | 0.17 | 29 | 0.18 | 27 | 0.15 | 31 |
| Mudanjiang | 0.26 | 7 | 0.25 | 6 | 0.28 | 6 | 0.28 | 7 | 0.29 | 8 |
| Heihe | 0.18 | 22 | 0.21 | 16 | 0.23 | 16 | 0.22 | 17 | 0.22 | 19 |
| Suihua | 0.14 | 33 | 0.14 | 31 | 0.14 | 34 | 0.13 | 34 | 0.12 | 34 |
| Changchun | 0.37 | 3 | 0.36 | 4 | 0.41 | 4 | 0.43 | 3 | 0.43 | 4 |
| Jilin | 0.22 | 12 | 0.22 | 13 | 0.24 | 13 | 0.25 | 14 | 0.26 | 12 |
| Siping | 0.14 | 31 | 0.16 | 25 | 0.18 | 28 | 0.18 | 26 | 0.18 | 25 |
| Liaoyuan | 0.19 | 19 | 0.15 | 28 | 0.15 | 33 | 0.16 | 33 | 0.14 | 32 |
| Tonghua | 0.15 | 28 | 0.15 | 29 | 0.17 | 30 | 0.21 | 22 | 0.18 | 26 |
| Baishan | 0.16 | 27 | 0.17 | 24 | 0.17 | 31 | 0.16 | 32 | 0.13 | 33 |
| Songyuan | 0.17 | 26 | 0.19 | 19 | 0.21 | 23 | 0.25 | 13 | 0.22 | 18 |
| Baicheng | 0.20 | 14 | 0.23 | 10 | 0.21 | 19 | 0.26 | 11 | 0.24 | 13 |
| Shenyang | 0.56 | 2 | 0.51 | 2 | 0.58 | 2 | 0.57 | 2 | 0.61 | 2 |
| Dalian | 0.68 | 1 | 0.58 | 1 | 0.67 | 1 | 0.68 | 1 | 0.71 | 1 |
| Anshan | 0.27 | 6 | 0.25 | 7 | 0.27 | 9 | 0.27 | 8 | 0.31 | 7 |
| Fushun | 0.18 | 21 | 0.18 | 21 | 0.21 | 22 | 0.21 | 23 | 0.23 | 17 |
| Benxi | 0.18 | 23 | 0.17 | 23 | 0.21 | 21 | 0.21 | 19 | 0.24 | 16 |
| Dandong | 0.22 | 11 | 0.24 | 9 | 0.28 | 8 | 0.26 | 10 | 0.26 | 11 |
| Jinzhou | 0.20 | 15 | 0.23 | 12 | 0.26 | 10 | 0.26 | 9 | 0.27 | 9 |
| Yingkou | 0.25 | 8 | 0.24 | 8 | 0.28 | 7 | 0.29 | 6 | 0.31 | 6 |
| Fuxin | 0.14 | 30 | 0.14 | 32 | 0.20 | 24 | 0.17 | 28 | 0.20 | 21 |
| Liaoyang | 0.22 | 10 | 0.22 | 14 | 0.23 | 14 | 0.22 | 16 | 0.24 | 14 |
| Panjin | 0.24 | 9 | 0.23 | 11 | 0.25 | 12 | 0.26 | 12 | 0.27 | 10 |
| Tieling | 0.21 | 13 | 0.21 | 15 | 0.22 | 18 | 0.21 | 21 | 0.19 | 22 |
| Chaoyang | 0.17 | 25 | 0.15 | 27 | 0.20 | 25 | 0.20 | 24 | 0.18 | 23 |
| Huludao | 0.12 | 34 | 0.14 | 34 | 0.16 | 32 | 0.17 | 29 | 0.17 | 28 |
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| Harbin | 0.54 | 4 | 0.55 | 4 | 0.60 | 3 | 0.67 | 2 | ||
| Qiqihar | 0.25 | 13 | 0.21 | 18 | 0.23 | 14 | 0.24 | 14 | ||
| Jixi | 0.18 | 27 | 0.18 | 25 | 0.20 | 19 | 0.18 | 27 | ||
| Hegang | 0.17 | 29 | 0.16 | 30 | 0.15 | 30 | 0.16 | 32 | ||
| Shuangyashan | 0.23 | 17 | 0.18 | 23 | 0.14 | 32 | 0.16 | 31 | ||
| Daqing | 0.39 | 5 | 0.38 | 5 | 0.39 | 5 | 0.38 | 5 | ||
| Yichun | 0.18 | 26 | 0.17 | 28 | 0.18 | 25 | 0.18 | 29 | ||
| Jiamusi | 0.22 | 18 | 0.19 | 20 | 0.22 | 17 | 0.18 | 28 | ||
| Qitaihe | 0.19 | 25 | 0.16 | 31 | 0.17 | 27 | 0.18 | 26 | ||
| Mudanjiang | 0.33 | 6 | 0.28 | 7 | 0.23 | 13 | 0.29 | 7 | ||
| Heihe | 0.21 | 22 | 0.18 | 24 | 0.23 | 15 | 0.20 | 20 | ||
| Suihua | 0.12 | 34 | 0.11 | 34 | 0.12 | 33 | 0.13 | 34 | ||
| Changchun | 0.57 | 3 | 0.62 | 1 | 0.67 | 2 | 0.50 | 4 | ||
| Jilin | 0.28 | 9 | 0.29 | 6 | 0.32 | 6 | 0.27 | 10 | ||
| Siping | 0.17 | 30 | 0.18 | 26 | 0.22 | 18 | 0.19 | 21 | ||
| Liaoyuan | 0.16 | 32 | 0.17 | 29 | 0.18 | 26 | 0.19 | 24 | ||
| Tonghua | 0.19 | 24 | 0.22 | 15 | 0.24 | 11 | 0.23 | 16 | ||
| Baishan | 0.15 | 33 | 0.13 | 33 | 0.15 | 31 | 0.15 | 33 | ||
| Songyuan | 0.26 | 12 | 0.24 | 12 | 0.28 | 7 | 0.27 | 8 | ||
| Baicheng | 0.29 | 8 | 0.27 | 8 | 0.28 | 8 | 0.26 | 12 | ||
| Shenyang | 0.58 | 2 | 0.56 | 3 | 0.57 | 4 | 0.59 | 3 | ||
| Dalian | 0.59 | 1 | 0.58 | 2 | 0.67 | 1 | 0.72 | 1 | ||
| Anshan | 0.30 | 7 | 0.26 | 10 | 0.26 | 9 | 0.29 | 6 | ||
| Fushun | 0.22 | 20 | 0.21 | 17 | 0.20 | 21 | 0.21 | 18 | ||
| Benxi | 0.25 | 15 | 0.22 | 14 | 0.17 | 28 | 0.19 | 22 | ||
| Dandong | 0.22 | 19 | 0.19 | 22 | 0.19 | 23 | 0.20 | 19 | ||
| Jinzhou | 0.27 | 10 | 0.26 | 9 | 0.23 | 16 | 0.27 | 11 | ||
| Yingkou | 0.27 | 11 | 0.23 | 13 | 0.25 | 10 | 0.27 | 9 | ||
| Fuxin | 0.20 | 23 | 0.19 | 21 | 0.18 | 24 | 0.18 | 25 | ||
| Liaoyang | 0.23 | 16 | 0.22 | 16 | 0.20 | 20 | 0.23 | 15 | ||
| Panjin | 0.25 | 14 | 0.25 | 11 | 0.23 | 12 | 0.26 | 13 | ||
| Tieling | 0.21 | 21 | 0.20 | 19 | 0.20 | 22 | 0.22 | 17 | ||
| Chaoyang | 0.17 | 28 | 0.17 | 27 | 0.16 | 29 | 0.19 | 23 | ||
| Huludao | 0.16 | 31 | 0.14 | 32 | 0.10 | 34 | 0.16 | 30 | ||
Figure 3Variations of urban vitality of cities in three northeastern provinces of China from 2010 to 2018. Note: In order to visualize the results better, the municipal districts are shown as administrative regions. And (a–i) respectively correspond to the subfigures of 2010–2018, marking their correct order.
The correlation coefficient between urban shrinkage and urban vitality.
| Correlation Coefficient | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 |
|---|---|---|---|---|---|---|---|---|---|
| Urban vitality | 0.386 | 0.451 | 0.438 | 0.469 | 0.488 | 0.457 | 0.463 | 0.437 | 0.457 |
| Economic vitality | 0.363 | 0.401 | 0.386 | 0.402 | 0.411 | 0.398 | 0.426 | 0.408 | 0.401 |
| Social vitality | 0.123 | 0.182 | 0.165 | 0.262 | 0.326 | 0.235 | 0.344 | 0.276 | 0.249 |
| Cultural vitality | 0.467 | 0.446 | 0.485 | 0.446 | 0.449 | 0.403 | 0.360 | 0.321 | 0.269 |
| Environmental vitality | 0.291 | 0.371 | 0.305 | 0.307 | 0.562 | 0.437 | 0.369 | 0.434 | 0.609 |
| Spatial vitality | 0.172 | 0.164 | 0.113 | 0.154 | 0.088 | −0.029 | 0.01 | −0.068 | 0.149 |