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通过多变量方法和模型衡量城市空间中的社会脆弱性。

Measuring Social Vulnerability in an Urban Space Through Multivariate Methods and Models.

作者信息

Davino Cristina, Gherghi Marco, Sorana Silvia, Vistocco Domenico

机构信息

Department of Economics and Statistics, University of Naples Federico II, Naples, Italy.

Department of Political Sciences, Communications and International Relationships, University of Macerata, Macerata, Italy.

出版信息

Soc Indic Res. 2021;157(3):1179-1201. doi: 10.1007/s11205-021-02680-0. Epub 2021 Apr 28.

DOI:10.1007/s11205-021-02680-0
PMID:33935346
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8080097/
Abstract

This article proposes a quantitative analysis to measure social vulnerability in a urban space, specifically in the area of the Municipality of Rome. Social vulnerability can be defined as a situation in which people are characterized by a condition of multidimensional deprivation that encompasses multiple aspects of life and exposes population to different risks and hazards produced by natural, environmental, socioeconomic and epidemic factors. The analysis that follows presents the use of multivariate methods and models to provide an index for every dimensions of vulnerability (housing quality, social context, education, employment, urban mobility, social relations and economic conditions) and a global index for mapping social vulnerability. The analysis also succeeds in identifying significant vulnerability spatial patterns and to measure how and if vulnerability can be different in case of an observed heterogeneity in urban space.

摘要

本文提出一种定量分析方法，以衡量城市空间，特别是罗马市辖区内的社会脆弱性。社会脆弱性可定义为这样一种状况：人们处于多维贫困状态，这种贫困涵盖生活的多个方面，并使人口面临自然、环境、社会经济和流行病因素产生的不同风险与危害。接下来的分析展示了如何运用多元方法和模型，为脆弱性的各个维度（住房质量、社会环境、教育、就业、城市交通、社会关系和经济状况）提供一个指数，并为绘制社会脆弱性提供一个综合指数。该分析还成功识别出显著的脆弱性空间模式，并衡量在城市空间存在观测到的异质性情况下，脆弱性如何以及是否会有所不同。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/08d377444adc/11205_2021_2680_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/2b3d02e57340/11205_2021_2680_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/3f878d6aff27/11205_2021_2680_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/bb3c9f7287ac/11205_2021_2680_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/59fec42b133d/11205_2021_2680_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/3777b030af5d/11205_2021_2680_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/d30878e2b574/11205_2021_2680_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/9fbd3e45d6de/11205_2021_2680_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/0df8a3460a0b/11205_2021_2680_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/08d377444adc/11205_2021_2680_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/2b3d02e57340/11205_2021_2680_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/3f878d6aff27/11205_2021_2680_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/bb3c9f7287ac/11205_2021_2680_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/59fec42b133d/11205_2021_2680_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/3777b030af5d/11205_2021_2680_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/d30878e2b574/11205_2021_2680_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/9fbd3e45d6de/11205_2021_2680_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/0df8a3460a0b/11205_2021_2680_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85dd/8080097/08d377444adc/11205_2021_2680_Fig9_HTML.jpg

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