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2025 , Vol. 48 >Issue 1: 130 - 142

DOI: https://doi.org/10.12118/j.issn.1000-6060.2024.101

区域发展

黄河流域城市生态韧性、社会网络及其影响因素分析

  • 张傲翔 ,
  • 苗成林 ,
  • 陈峥妍
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  • 1.安徽理工大学经济与管理学院，安徽 淮南 232001
    2.山东工商学院工商管理学院，山东 烟台 264005
张傲翔（1998-），男，硕士研究生，主要从事技术创新与管理研究. E-mail: aoxiangzhg@163.com
苗成林（1980-），男，博士，教授，主要从事绿色低碳发展、创新管理与政策研究. E-mail: chlmiaostbu@163.com

收稿日期: 2024-02-20

  修回日期: 2024-04-11

  网络出版日期: 2025-01-21

基金资助

国家自然科学基金面上项目(72173073);国家自然科学基金面上项目(51774013);国家自然科学基金面上项目(71503003);2021年度烟台市校地融合发展项目(2021XDRHXMXK06);安徽理工大学2023年研究生创新基金项目(2023CX2168)

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Urban ecological resilience, social networks and its influencing factors in the Yellow River Basin

  • ZHANG Aoxiang ,
  • MIAO Chenglin ,
  • CHEN Zhengyan
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  • 1. School of Economics and Management, Anhui University of Science and Technology, Huainan 232001, Anhui, China
    2. School of Business Administration, Shandong Technology and Business University, Yantai 264005, Shandong, China

Received date: 2024-02-20

  Revised date: 2024-04-11

  Online published: 2025-01-21

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摘要

分析城市生态韧性的社会网络以及影响因素有助于促进区域绿色协同发展。选取黄河流域63个地级市2012—2021年相关数据，构建压力-状态-反应模型。采用CRITIC-TOPSIS、引力模型、多尺度地理加权回归模型分析黄河流域城市生态韧性、联动关系以及影响因素。结果表明：（1） 黄河流域生态韧性总体在0.5左右波动，表现为“上游>下游>中游”，各流域年平均涨幅分别为0.41%、0.30%、0.40%。（2） 黄河流域大致可分为7个主要城市网络（N1~N7），上、中、下游的流域聚集程度和城市关联程度依次不断升高。（3） 考虑直接作用、调节作用以及替代效应的影响，产业结构高级化对城市网络N1~N4的城市生态韧性提升作用更大，影响系数分别为0.4213、0.4210、0.5085、0.8883，而产业结构合理化更有利于提升城市网络N5~N7的城市生态韧性，影响系数分别为0.8483、0.5669、0.8128。

关键词： 生态韧性; 空间结构; CRITIC-TOPSIS; 多尺度地理加权回归; 黄河流域

本文引用格式

张傲翔 , 苗成林 , 陈峥妍 . 黄河流域城市生态韧性、社会网络及其影响因素分析[J]. 干旱区地理, 2025 , 48(1) : 130 -142 . DOI: 10.12118/j.issn.1000-6060.2024.101

Abstract

The social network of urban ecological resilience and its influencing factors were analyzed to promote regional green synergistic development. Data from 2012 to 2021 for 63 prefecture-level cities in the Yellow River Basin, China, were used to construct a pressure-state-response model. The CRITIC-TOPSIS method, gravity model, and multi-scale geographic weighting model were applied to examine the ecological resilience of cities in the Yellow River Basin, the linkage relationships, and the influencing factors. The results reveal the following: (1) The ecological resilience of the Yellow River Basin fluctuates around 0.5, with the pattern “upstream>downstream>midstream”, and the average annual increase rates of each river reach was 0.41%, 0.30%, and 0.40%, respectively. (2) The Yellow River Basin is divided into seven major city networks (N1-N7). The degree of basin agglomeration and city association increases sequentially from the upper to the lower reaches. (3) Considering the influence of direct effect, regulatory effect and substitution effect, industrial structure upgrades significantly enhance the urban ecological resilience of city networks N1-N4, with impact coefficients of 0.4213, 0.4210, 0.5085, and 0.8883, respectively. In contrast, industrial structure rationalization more effectively enhances the ecological resilience of city networks N5-N7, with impact coefficients of 0.8483, 0.5669, and 0.8128.

Key words： ecological resilience; spatial structure; CRITIC-TOPSIS; multi-scale geographical weighted regression; Yellow River Basin

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