黄河流域城市生态韧性、社会网络及其影响因素分析

doi:10.12118/j.issn.1000-6060.2024.101

摘要/Abstract

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

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

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.

ZHANG Aoxiang, MIAO Chenglin, CHEN Zhengyan. Urban ecological resilience, social networks and its influencing factors in the Yellow River Basin[J]. Arid Land Geography, 2025, 48(1): 130-142.

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目标层	准则层	指标层	单位	属性	权重
城市生态韧性	压力	SO₂排放量	t	负	0.1198
		工业烟（粉）尘排放量	t	负	0.0844
		自然灾害频率	次·a^-1	负	0.0854
	状态	人均公园绿地面积	m²·人^-1	正	0.0580
		空气质量优良率	%	正	0.1699
		建成区绿化覆盖率	%	正	0.0759
	反应	节能环保支出占一般财政支出的比重	%	正	0.0825
		污水处理率	%	正	0.0898
		一般工业固体废弃物综合利用率	%	正	0.1662
		城市生活垃圾无害化处理率	%	正	0.0680

检验参数	模型1		模型2		模型3
检验参数	GWR	MGWR	GWR	MGWR	GWR	MGWR
残差标准误（Sigma estimate）	0.678	0.661	0.77	0.756	0.592	0.573
最大似然估计（Log-likelihood）	-66.818	-65.060	-75.859	-74.818	-54.843	-53.514
赤池信息量准则（AIC）	155.259	151.827	172.839	169.984	139.678	133.964
校正赤池信息量准则（AICc）	159.649	156.252	177.018	173.849	148.562	140.981
贝叶斯信息准则（BIC）	179.571	176.231	196.585	192.860	173.397	164.246
决定系数（R²）	0.605	0.624	0.489	0.504	0.719	0.730
校正决定系数（Adj. R²）	0.539	0.562	0.406	0.427	0.648	0.670

城市网络	模型1		模型2		模型3
城市网络	Coff_X₁	R²	Coff_X₂	R²	Coff_X₁	Coff_X₂	Coff_X₁×X₂	R²
N₁	0.4213^***	0.5040	0.2864^**	0.2734	-0.0465	0.4305^*	-0.2640	0.6079
N₁	(3.6453)		(-2.2599)		(-0.4107)	(-1.7313)	(-0.1196)
N₂	0.4210^***	0.5787	0.3010^**	0.4222	-0.0921	0.4799^*	-0.2049	0.6916
N₂	(3.7700)		(-2.3833)		(-0.8228)	(-1.9695)	(-0.0929)
N₃	0.5085^***	0.4664	0.2403^*	0.2076	0.1051	0.4924^**	-0.3048	0.5579
N₃	(4.3572)		(-1.9777)		-0.9493	(-2.0408)	(-0.1380)
N₄	0.8883^***	0.6393	0.1142	0.5321	0.1544	0.9697^***	0.0076	0.7692
N₄	(6.2403)		(-0.6300)		-1.2428	(-4.6244)	-0.0034
N₅	0.6221^***	0.5925	0.5801^***	0.5457	-0.1233	0.8483^***	0.3150	0.7608
N₅	(4.6876)		(-2.7459)		(-0.9382)	(-3.9456)	-0.1403
N₆	0.4263^***	0.5539	0.3667^***	0.4599	-0.1791	0.5669^**	-0.0859	0.7085
N₆	(3.3686)		(-2.9261)		(-1.4340)	(-2.3460)	(-0.0389)
N₇	0.5679^***	0.6319	0.4975^**	0.5536	-0.1293	0.8128^***	0.2121	0.7418
N₇	(4.3848)		(-2.4187)		(-1.0116)	(-3.8533)	-0.0946
控制变量	是		是		是