RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN >> 2023, Vol. 32 >> Issue (11): 2312-2325.doi: 10.11870/cjlyzyyhj202311007

Previous Articles     Next Articles

Spatial-temporal Evolution Characteristics and Dynamic Prediction of Urban Resilience in Urban Agglomerations in Middle Reaches of Yangtze River

YIN Jian-jun1,2, HU Jing1, HUANG Yu-xuan1   

  1. (1. College of Urban and Environmental Science, Central China Normal University/ Wuhan Branch of China Tourism Academy, Wuhan 430070, China; 2. School of Geography and Tourism, Huanggang Normal University, Huanggang 430081, China)
  • Online:2023-11-20 Published:2023-11-28

Abstract: With the increasing attention of urban development risk governance research, urban resilience has become a hot topic in this field. selecting 26 prefecture-level cities in the urban agglomeration in the middle reaches of the Yangtze River as the research objecton urban resilience indicators from 2006 to 2021 evolutionary resilience theory employ entropy evaluation method to measure the level of urban resiliencehe spatial-temporal evolution characteristics of urban resilience the main influence factors of urban resilience evolution panel data regression models finally the development trend of urban resilience  through gray prediction models. The research results indicate that: (1) During the research period, the overall level of urban resilience in the urban agglomeration in the middle reaches of the Yangtze River s relatively low, with a slow, sustained and steady growth trend in urban resilience significant regional differences, small dispersion, and a slow convergence trend; Regions with high resilience  while low resilience regions widely distributed, which basically formed the ‘core-periphery’ spatial pattern of regular triangular shape with high resilient zone at the apex, medium and low resilient zones at the edge.(2) The intensity of openness, diversification of industrial structure, and urbanization level the main influencfactors the development and change of urban resilience in the region, with urbanization level having the greatest impact, the intensity of openness and diversification of industrial structure having slightly weaker impact, and administrative and innovation capabilities having no significant impact on urban resilience. Therefore, it is necessary to further improve regional administrative management and innovation capabilities. (3) In the future, the urban resilience of the research area still exhibit a steady growth trend, and the overall level of urban resilience will be significantly improved. Regions with high resilience will significantly increase, and regional differences might be expanding. The core position of regional central cities such as Wuhan, Changsha, Nanchang, and Zhuzhou will be further, and the “core-periphery” urban resilience spatial pattern will be further stabilized.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] YAO Lin, SHEN Jing, WEN Xinlong, GAO Chao. Impact of Various Parameterization Schemes in WRF Model on Wind Simulation at the mountain Wind Power Station of Jiangxi Province[J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2018, 27(07): 1380 .
[2] SUN Huihui, ZHANG Xinping, LUO Zidong, SHANG ChengPeng, HE Xinguang, RAO Zhiguo. Analyses on Characteristics of Extreme Precipitation Indices in the #br# Yangtze River Basin in the Past 53 Years#br#[J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2018, 27(08): 1879 .
[3] WANG Lei, LI Cheng-li.  

The Effect of Multi-Center Structure of Urban Agglomerations in Central China [J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2018, 27(10): 2231 -2240 .

[4] FANG Lin, , WU Fengping, WANG Xinhua, YU Yantuan.  

Analysis of Agricultural Water Efficiency Measurement and Improvement Potential Based on Meta Frontier SBM Model [J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2018, 27(10): 2293 -2304 .

[5] LV Le-ting, WANG Xiao-rui, SUN Cai-zhi, ZHANG Jie. Study on the Spatiotemporal Variations of Blue and Green Water Resources in Xi River Basin Using the SWAT Model[J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2019, 28(01): 39 -47 .
[6] LI Yan, MA Bai-sheng, YANG Xuan. Impact of Two Types of ENSO Events on the Extreme Precipitation in Eastern China[J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2019, 28(02): 469 -482 .
[7] KE Hang, WANG Xiao-jun, YIN Yi-xing, LUO Zhi-wen, . Spatial and Temporal Characteristics of Extreme Precipitation and Drought in Hengshui City from 1961 to 2015[J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2019, 28(04): 971 -980 .
[8] HAN Jing, RUI Yang, MA Teng, WU Peng, CHAO Jing. Evolution and Influencing Factors of Inter Provincial Distribution Pattern of National Garden Counties[J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2019, 28(04): 829 -838 .
[9] ZHONG Ye-xi, GUO Wei-dong, MAO Wei-sheng, WANG Xiao-jing, FENG Xing-hua. Urban Railway Network and Accessibility Evolution Research of the “Min Xin Axis Belt”[J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2019, 28(05): 1015 -1024 .
[10] LI Jing-zhi, DAI Yu-han, ZHAO Wen, FAN Chen-xi, LUO Wen-jing, XIONG Ying, ZHANG Yong-zhi, TANG Li-sha. Study on Spatial-Temporal Characteristics of Interaction Coupling Between Regional Urbanization System and Ecosystem and Early-warning of Coordinated Development: A Case of Hunan Province[J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2019, 28(07): 1590 -1601 .