Regional Sustainability >

2024 , Vol. 5 >Issue 3: 100159

DOI: https://doi.org/10.1016/j.regsus.2024.100159

Full Length Article

Spatiotemporal evolution and influencing factors of urban resilience in the Yellow River Basin, China

  • JI Xiaomei ,
  • NIE Zhilei ,
  • WANG Kaiyong ,
  • XU Mingxian ,
  • FANG Yuhao
Expand
  • aQilu University of Technology (Shandong Academy of Sciences), Jinan, 250100, China
    bScience and Technology Service Platform of Shandong Academy of Sciences (Pioneer Park for Overseas Students of Shandong Academy of Sciences), Jinan, 250100, China
    cInstitute of Science and Technology for Development of Shandong, Jinan, 250014, China
    dInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
* E-mail address: nzl18340088159@126.com (NIE Zhilei)

Received date: 2023-08-31

  Revised date: 2024-04-18

  Accepted date: 2024-08-22

  Online published: 2024-09-25

Fold

Abstract

The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment. Industrialization and urbanization promote social-economic development, but they also have generated a series of environmental and ecological issues in this basin. Previous researches have evaluated urban resilience at the national, regional, urban agglomeration, city, and prefecture levels, but not at the watershed level. To address this research gap and elevate the Yellow River Basin’s urban resilience level, we constructed an urban resilience evaluation index system from five dimensions: industrial resilience, social resilience, environmental resilience, technological resilience, and organizational resilience. The entropy weight method was used to comprehensively evaluate urban resilience in the Yellow River Basin. The exploratory spatial data analysis method was employed to study the spatiotemporal differences in urban resilience in the Yellow River Basin in 2010, 2015, and 2020. Furthermore, the grey correlation analysis method was utilized to explore the influencing factors of these differences. The results of this study are as follows: (1) the overall level of urban resilience in the Yellow River Basin was relatively low but showed an increasing trend during 2010-2015, and significant spatial distribution differences were observed, with a higher resilience level in the eastern region and a low-medium resilience level in the western region; (2) the differences in urban resilience were noticeable, with industrial resilience and social resilience being relatively highly developed, whereas organizational resilience and environmental resilience were relatively weak; and (3) the correlation ranking of resilience influencing factors was as follows: science and technology level>administrative power>openness>market forces. This research can provide a basis for improving the resilience level of cities in the Yellow River Basin and contribute to the high-quality development of the region.

Key words： Urban resilience; Spatiotemporal evolution; Entropy weight method; Exploratory spatial data analysis method; Grey correlation analysis method; Yellow River Basin

Cite this article

JI Xiaomei , NIE Zhilei , WANG Kaiyong , XU Mingxian , FANG Yuhao . Spatiotemporal evolution and influencing factors of urban resilience in the Yellow River Basin, China[J]. Regional Sustainability, 2024 , 5(3) : 100159 . DOI: 10.1016/j.regsus.2024.100159

References

[1] Berkes F., Folke C., 1998. Linking Social and Ecological Systems for Resilience and Sustainability. Cambridge: Cambridge University Press, 13-20.
[2] Bozza A., Asprone D., Manfredi G., 2015. Developing an integrated framework to quantify resilience of urban systems against disasters. Nat. Hazards. 78(3), 1729-1748.
[3] Carpenter S., Walker B., Anderies M.J., et al., 2001. From metaphor to measurement: Resilience of what to what? Ecosystems. 4(8), 765-781.
[4] Cavallaro M., Asprong D., Latora V., et al., 2014. Assessment of urban ecosystem resilience through Hybrid Social-Physical complex networks. Comput-Aided. Civ. Inf. 29(8), 608-625.
[5] Chelleri L., Baravikova A., 2021. Understandings of urban resilience meanings and principles across Europe. Cities. 108, 102985, doi: 10.1016/j.cities.2020.102985.
[6] Chen X.H., Lou J.N., Wang Y., 2020. Evolution and dynamic simulation of the temporal-spatial pattern of urban resilience in Harbin-Changchun Urban Group. Scientia Geographica Sinica. 40(12), 2000-2009 (in Chinese).
[7] Chen Y., Li K.Y., Zhou Q., 2023. Spatial differentiation of urban economic resilience and its influencing factors: Evidence from Baidu migration big data. Technol. Econ. Dev. Eco. 29(2), 353-381.
[8] Chen Y.M., Huang Y.X., Li K.C., et al., 2019. Dimensions and measurement of city resilience in theory and in practice. In:Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance. Melbourne: Association for Computing Machinery.
[9] Cheng Y.R., Liu J.H., 2023. Evaluation of urban resilience in the post-COVID-19 period: A case study of the Yangtze delta city group in China. Int. J. Disast. Risk. Re. 97, 104028, doi: 10.1016/j.ijdrr.2023.104028.
[10] Cutter S.L., Ash K.D., Emrich C.T., 2016. Urban-rural differences in disaster resilience. Ann. Am. Assoc. Geogr. 106(6), 1236-1252.
[11] Deng J.L., 1990. Tutorial on Grey System Theory. WuHan: Huazhong University of Technology Press (in Chinese).
[12] Ding J.J., Wang Z., Liu Y.H., et al., 2020. Measurement of economic resilience of contiguous poverty-stricken areas in China and influencing factor analysis. Progress in Geography. 39(6), 924-937 (in Chinese).
[13] Dong X.J., Shi T., Zhang W., et al., 2020. Temporal and spatial differences in the resilience of smart cities and their influencing factors: Evidence from Non-Provincial cities in China. Sustainability. 12(4), 1321, doi: 10.3390/su12041321.
[14] Eledi Kuusaana J.A., Monstadt J., Smith S., 2023. Toward urban resilience? Coping with blackouts in Dar es Salaam, Tanzania. J. Urban. Technology. 30(2), 79-101.
[15] Fang C.L., Wang Y., Fang J.W., 2016. A comprehensive assessment of urban vulnerability and its spatial differentiation in China. J. Geogr. Sci. 26(2), 153-170.
[16] Feofilovs M., Romagnoli F., 2021. Dynamic assessment of urban resilience to natural hazards. Int. J. Disaster Risk. Re. 62, 102328, doi: 10.1016/j.ijdrr.2021.102328.
[17] Gansu Provincial Bureau of Statistics, 2011. Gansu Development Yearbook. Beijing: China Statistics Press (in Chinese).
[18] Gansu Provincial Bureau of Statistics, 2016. Gansu Development Yearbook. Beijing: China Statistics Press (in Chinese).
[19] Gansu Provincial Bureau of Statistics, 2021. Gansu Development Yearbook. Beijing: China Statistics Press (in Chinese).
[20] Gao Z.G., Ding Y.Y., 2021. Measurement of urban resilience and its influencing factors in Northwest China. Science & Technology Review. 39(24), 118-129 (in Chinese).
[21] Golubchikov O., DeVerteuil G., 2021. Urban Inequalities and the Lived Politics of Resilience. Volume 4: Policy and Planning. Bristol: Bristol University Press, 69-78.
[22] He B.J., Zhao D.X., Zhu J., et al., 2018. Promoting and implementing urban sustainability in China: An integration of sustainable initiatives at different urban scales. Habitat. Int. 82, 83-93.
[23] He S.F., Liang S., Wu S.H., et al, 2022. Spatial and temporal evolution of urban flood resilience in the Yangtze River Delta region and its correlation analysis. Yangtze River Basin Resources and Environment. 31(9), 1988-1999 (in Chinese).
[24] Henan Provincial Bureau of Statistics, 2011. Henan Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[25] Henan Provincial Bureau of Statistics, 2016. Henan Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[26] Henan Provincial Bureau of Statistics, 2021. Henan Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[27] Holling C.S., 1973. Resilience and stability of ecological systems. Annu. Rev. Ecol. Syst. 4(1), 1-23.
[28] Hou X., Ma Q.L., Wang, X., 2021. Spatial differentiation and elements influencing urban resilience in the middle reaches of the Yangtze River under the COVID-19 pandemic. Discrete Dyn. Nat. Soc. doi: 10.1155/2021/6687869.
[29] Inner Mongolia Autonomous Region Bureau of Statistics, 2011. Inner Mongolia Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[30] Inner Mongolia Autonomous Region Bureau of Statistics, 2016. Inner Mongolia Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[31] Inner Mongolia Autonomous Region Bureau of Statistics, 2021. Inner Mongolia Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[32] Ji X.M., Nie Z.L., Liang H.Y., 2022. Evaluation of changes in urban resilience and analysis of influencing factors Jinan City, Shandong Province as an example. Science and Management. 42(3), 87-94 (in Chinese).
[33] Li H.Y., Wang Y., Zhang H.W., et al., 2024. The spatial-temporal evolution and driving mechanism of urban resilience in the Yellow River Basin cities. J. Clean. Prod. 447, 141614, doi: 10.1016/j.jclepro.2024.141614.
[34] Li M.J., Liu D.L., 2022. Spatial and temporal evolution of urban disaster resilience and barrier factors in the Zhongyuan urban agglomeration. Chinese Journal of Safety Science. 32(9), 144-151 (in Chinese).
[35] Li Y.T., Chen T., Wang Y.L., 2023. Grey forecasting the impact of population and GDP on the carbon emission in a Chinese region. J. Clean Production. 425, 139025, doi: 10.1016/j.jclepro.2023.139025.
[36] Liao Z.J., Zhang L.J., 2024. Spatio-temporal pattern evolution and dynamic simulation of urban ecological resilience in Guangdong Province, China. Heliyon. 10(3), e25127, doi: 10.1016/j.heliyon.2024.e25127.
[37] Lu H., Lu X., Jiao L.D., et al., 2022. Evaluating urban agglomeration resilience to disaster in the Yangtze Delta city group in China. Sustainable Cities. 76, 103464, doi: 10.1016/j.scs.2021.103464.
[38] Maru M., Worku H., Bikmann J., 2021. Factors affecting the spatial resilience of Ethiopia’s secondary cities to urban uncertainties: A study of household perceptions of Kombolcha city. Heliyon. 7(12), e08472, doi: 10.1016/j.heliyon.2021.e08472.
[39] Ministry of Housing and Urban-Rural Development of China, 2011. China Urban-Rural Construction Statistical Yearbook. Beijing: China Planning Press (in Chinese).
[40] Ministry of Housing and Urban-Rural Development of China, 2016. China Urban-Rural Construction Statistical Yearbook. Beijing: China Planning Press (in Chinese).
[41] Ministry of Housing and Urban-Rural Development of China, 2021. China Urban-Rural Construction Statistical Yearbook. Beijing: China Planning Press (in Chinese).
[42] Nathwani J., Lu X.L., Wu C.Y., et al., 2019. Quantifying security and resilience of Chinese coastal urban ecosystems. Sci. Total Environ. 672, 51-60.
[43] National Bureau of Statistics of China, 2011a. China Statistical Yearbook for Regional Economy. Beijing: China Statistics Press (in Chinese).
[44] National Bureau of Statistics of China, 2011b. China City Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[45] National Bureau of Statistics of China, 2016a. China Statistical Yearbook for Regional Economy. Beijing: China Statistics Press (in Chinese).
[46] National Bureau of Statistics of China, 2016b. China City Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[47] National Bureau of Statistics of China, 2021a. China Statistical Yearbook for Regional Economy. Beijing: China Statistics Press (in Chinese).
[48] National Bureau of Statistics of China, 2021b. China City Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[49] National Bureau of Statistics of China, 2023. China Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[50] Ningxia Autonomous Region Bureau of Statistics, 2011. Ningxia Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[51] Ningxia Autonomous Region Bureau of Statistics, 2016. Ningxia Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[52] Ningxia Autonomous Region Bureau of Statistics, 2021. Ningxia Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[53] Qinghai Provincial Bureau of Statistics, 2011. Qinghai Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[54] Qinghai Provincial Bureau of Statistics, 2016. Qinghai Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[55] Qinghai Provincial Bureau of Statistics, 2021. Qinghai Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[56] Resilience Alliance, 2007. Urban Resilience Research Prospectus. Australia: CSIRO.
[57] Sandu A., Banica A., Muntele I., 2021. Urban resilience: An instrument to decode the postsocialist socio-economic and spatial transformations of cities from Central and Eastern Europe. East. J. Eur. Stud. 12(Special Issue), 170-195.
[58] Shaanxi Provincial Bureau of Statistics, 2011. Shaanxi Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[59] Shaanxi Provincial Bureau of Statistics, 2016. Shaanxi Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[60] Shaanxi Provincial Bureau of Statistics, 2021. Shaanxi Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[61] Shandong Provincial Bureau of Statistics, 2011. Shandong Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[62] Shandong Provincial Bureau of Statistics, 2016. Shandong Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[63] Shandong Provincial Bureau of Statistics, 2021. Shandong Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[64] Shanxi Provincial Bureau of Statistics, 2011. Shanxi Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[65] Shanxi Provincial Bureau of Statistics, 2016. Shanxi Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[66] Shanxi Provincial Bureau of Statistics, 2021. Shanxi Statistical Yearbook. Beijing: China Statistics Press (in Chinese).
[67] Shao Y.W., Xu J., 2015. Understanding urban resilience: A conceptual analysis based on integrated international literature review. International Urban Planning. 30(2), 48-54 (in Chinese).
[68] Song Y.R., Dong X.J., 2022. The factors influencing the economic resilience of Chinese cities and the path of improvement. Lingnan Journal. (4), 97-105 (in Chinese).
[69] Soufi H.R., Esfahanipour A., Shirazi M.A., 2022. A quantitative approach for analysis of macroeconomic resilience due to socio-economic shocks. Socio-Econ. Plan. Sci. 79, 101101, doi: 10.1016/j.seps.2021.101101.
[70] Spaans M., Waterhout B., 2017. Building up resilience in cities worldwide-Rotterdam as participant in the 100 Resilient Cities Programme. Cities. 61, 109-116.
[71] Sun J., Liu S.D., Wang L., et al., 2020. Safety resilience evaluation of urban public bus based on comprehensive weighting method and fuzzy comprehensive evaluation method. In: International Conference on Urban Engineering and Management Science. Zhuhai, China.
[72] Sun J., Zhai N.N., Mu H.R., et al., 2024. Assessment of urban resilience and subsystem coupling coordination in the Beijing-Tianjin-Hebei urban agglomeration. Sustain. Cities. Soc. 100, 105058, doi: 10.1016/j.scs.2023.105058.
[73] Sun Y., Zhang L.C., Yao S.M., 2017. Evaluating resilience of prefecture cities in the Yangtze River delta region from a socio-ecological perspective. China Population, Resources and Environment. 27(8), 151-158 (in Chinese).
[74] Tao X.D., 2022. Resilient city construction in China: Connotation characteristics, shortcomings, and planning strategies. Urban Planning. 46(12), 28-34, 66 (in Chinese).
[75] Wang C.Y., Xu M., Olsson G., et al., 2020. Characterizing of water-energy-emission nexus of coal-fired power industry using entropy weighting method. resources. Resour. Conserv. Recy. 161, 104991, doi: 10.1016/j.resconrec.2020.104991.
[76] Wang Q.Z., Zhu Y.M., 2021. Research on economic resilience and influencing factors of Chinese cities. Ecological Economy. 37(10), 84-92 (in Chinese).
[77] Wang T.C., Lee H.D., 2009. Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert. Syst. Appl. 36(5), 8980-8985.
[78] Wu J.P., Pan Y.J., Luo H.S., et al., 2023. Study on the spatiotemporal pattern evolution and dynamic prediction of urban resilience in the central Yunnan urban agglomeration. Ecological Economy. 39(8), 95-105 (in Chinese).
[79] Xu Z.F., Tian J.F., Zhang J., 2019. Urban resilience evaluation system and optimization strategy from perspective of disaster prevention. China Safety Science Journal. 29(3), 1-7 (in Chinese).
[80] Yin J.J., Hu J., Huang Y.X., 2023. Study on the spatiotemporal evolution characteristics and dynamic prediction of urban resilience in the middle reaches of the Yangtze River Urban Agglomeration. Resources and Environment in the Yangtze Basin. 32(11), 2312-2325 (in Chinese).
[81] Yu J.L., Yang S.G., 2023. Study on the spatiotemporal differentiation and influencing factors of urban resilience level in the Yangtze River Delta. Economic System Reform. (6), 53-61 (in Chinese).
[82] Zhang M.D., Ren Y.T., Zhou L., 2023. Analysis of spatiotemporal evolution characteristics and influencing factors of urban ecological resilience in the Yellow River Basin. Arid Land Geography. 47(3), 445-454 (in Chinese).
[83] Zhang M.M., Chen W.G., Cai K., et al., 2019a. Analysis of the spatial distribution characteristics of urban resilience and its influencing factors: A case study of 56 cities in China. Int. J. Environ. Res. Public Health. 16(22), 4442, doi: 10.3390/ijerph16224442.
[84] Zhang M.M., Tan S.K., Pan Z.C., 2022. The spatial spillover effect and nonlinear relationship analysis between land resource misallocation and environmental pollution: Evidence from China. J. Environ. Manage. 321, 115873, doi: 10.1016/j.jenvman.2022.115873.
[85] Zhang X.S., Zhang M.M., He J., et al., 2019b. The spatial-temporal characteristics of cultivated land and its influential factors in the Low Hilly Region: A case study of Lishan Town, Hubei Province, China. Sustainability. 11(14), 3810, doi: 10.3390/su11143810.
[86] Zhao R.D., Fang C.L., Liu H.M., et al., 2021. Evaluating urban ecosystem resilience using the DPSIR framework and the ENA model: A case study of 35 cities in China. Sustain. Cities. Soc. 72, 102997, doi: 10.1016/j.scs.2021.102997.
[87] Zhao R.D., Fang C.L., Liu J., et al., 2022. The evaluation and obstacle analysis of urban resilience from the multidimensional perspective in Chinese cities. Sustain. Cities. Soc. 86, 104160, doi: 10.1016/j.scs.2022.104160.
[88] Zhou X., Wang J., 2024. Study on the spatiotemporal evolution characteristics and spatial differences of urban resilience in the Beijing Tianjin Hebei urban agglomeration: Based on an improved PSR framework. Resource Development and Market. 40(2), 231-239 (in Chinese).
[89] Zhu J.H., Sun H.X., 2020. A study on the spatial and temporal evolution of urban resilience and influencing factors in three major urban agglomerations in China. Soft Science. 34(2), 72-79 (in Chinese).
[90] Ziervogel G., Pelling M., Cartwright A., et al., 2017. Inserting rights and justice into urban resilience: A focus on everyday risk. Environ. Urban. 29(1), 123-138.
[91] Zou W., Wang X.Y., Wan F.J., et al., 2024. Research on the coupling and coordinated development of urban resilience and technological innovation level: Taking the Yangtze River Delta Urban Agglomeration as an example. Ecological Economy. 40(1), 78-87 (in Chinese).
Options
Outlines

/

〈 〉

Authors
  • Submit Online
  • Guide for Authors
  • Submission Template
  • Author Declaration Template
  • Ethical Policy
    • Reviewers
  • Reviewers Login
  • Tutorial for Reviewers
    • Contact
  • Tel: 86-991-7827334
    E-mail: regsus@ms.xjb.ac.cn
    Address: No. 818 South Beijing Road,
                   Urumqi 830011, Xinjiang, China
    • REGSUS Wechat
    • Copyright © Editorial Office of Regional Sustainability. All Rights Reserved.
    • 新ICP备06001700号-10　 新公网安备 65010402001202号