Suppr超能文献

黄河流域城市生态承载力的时空演变与空间网络分析。

Spatiotemporal Evolution and Spatial Network Analysis of the Urban Ecological Carrying Capacity in the Yellow River Basin.

机构信息

School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou 450001, China.

Economics School, Zhongnan University of Economics and Law, Wuhan 430073, China.

出版信息

Int J Environ Res Public Health. 2021 Dec 26;19(1):229. doi: 10.3390/ijerph19010229.

Abstract

Based on the panel data of 82 cities in the Yellow River Basin (YRB) during 2008-2017, this paper calculated the urban ecological carrying capacity (UECC) index by means of the entropy method, drew a spatiotemporal evolution map using ArcGIS10.3 software, used a spatial cold-hot spot model to explore the spatial characteristics of the UECC index, and used the revised gravity model to construct the spatial network of the UECC. In addition, through social network analysis, we obtained the spatial network correlation characteristics of the UECC of 82 cities in the YRB. The study found the following: (1) The UECC index of the cities in the YRB increased steadily, and showed strong non-stationarity in space. The cold and hot spot patterns both changed greatly. Overall, the changes of the hot and cold spots were very significant. (2) The spatial correlation and linkage effects of the UECC in the YRB were not significant. The central cities with higher point centrality and closeness centrality showed the same spatial distribution, and most of them are located in the midstream and downstream of the YRB. The central cities in the midstream and downstream of the YRB had high betweenness centrality, and stood in the center of the association network. (3) The four plates in the spatial correlation network of the UECC in the YRB all showed their advantages and functions. The first plate was the net spillover plate, which was principally allocated in the upstream and midstream of the YRB. The second plate was the broker plate, which was principally located in the midstream and downstream of the YRB, and a few cities in the upper reaches. The third plate was the net inflow plate, which was distributed sporadically in the upstream and downstream of the YRB. The fourth plate was the broker plate, which was scattered in upstream, midstream, and downstream of the YRB. Therefore, it is necessary to shorten the gap of and promote the improvement of the UECC in the YRB.

摘要

基于 2008-2017 年黄河流域 82 个城市的面板数据,本文运用熵值法计算城市生态承载能力(UECC)指数,利用 ArcGIS10.3 软件绘制时空演变图,采用空间冷热点模型探测 UECC 指数的空间特征,并利用修正的重力模型构建 UECC 的空间网络。此外,通过社会网络分析,获得了黄河流域 82 个城市 UECC 的空间网络关联特征。研究发现:(1)黄河流域城市 UECC 指数稳步增长,空间上表现出较强的非平稳性,冷热点格局变化较大,整体来看热点和冷点变化非常显著;(2)黄河流域 UECC 的空间相关性和联动效应不显著,点中心度和接近中心度较高的中心城市具有相同的空间分布,且多位于黄河流域中上游,中上游的中心城市具有较高的介数中心度,处于关联网络的中心位置;(3)黄河流域 UECC 空间关联网络的四大板块均表现出各自的优势和功能,第一板块为净溢出板块,主要配置在黄河流域的上游和中游,第二板块为中介板块,主要位于黄河流域的中下游以及上游的少数城市,第三板块为净流入板块,零星分布在黄河流域的上游和下游,第四板块为中介板块,零散分布在黄河流域的上、中、下游。因此,有必要缩小黄河流域 UECC 的差距,促进其提高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d37e/8751185/25bb6a8b5710/ijerph-19-00229-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验