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A Comparative Study of the Resilience of Urban and Rural Areas under Climate Change
The impact of climate change in recent years has caused considerable risks to both urban and rural systems. How to mitigate the damage caused by extreme weather events has attracted much attention from countries in recent years. However, most of the previous studies on resilience focused on either u...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9331052/ https://www.ncbi.nlm.nih.gov/pubmed/35897290 http://dx.doi.org/10.3390/ijerph19158911 |
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author | Su, Qingmu Chang, Hsueh-Sheng Pai, Shin-En |
author_facet | Su, Qingmu Chang, Hsueh-Sheng Pai, Shin-En |
author_sort | Su, Qingmu |
collection | PubMed |
description | The impact of climate change in recent years has caused considerable risks to both urban and rural systems. How to mitigate the damage caused by extreme weather events has attracted much attention from countries in recent years. However, most of the previous studies on resilience focused on either urban areas or rural areas, and failed to clearly identify the difference between urban and rural resilience. In fact, the exploration of the difference between the resilience characteristics of cities and villages under climate change can help to improve the planning strategy and the allocation of resources. In this study, the indicators of resilience were firstly built through a literature review, and then a Principal Component Analysis was conducted to construct an evaluation system involving indicators such as “greenland resilience”, “community age structure resilience”, “traditional knowledge resilience”, “infrastructure resilience” and “residents economic independence resilience”. Then the analysis of Local Indicators of Spatial Association showed some resilience abilities are concentrated in either urban or rural. Binary logistic regression was performed, and the results showed urban areas have more prominent abilities in infrastructure resilience (the coefficient value is 1.339), community age structure resilience (0.694), and greenland resilience (0.3), while rural areas are more prominent in terms of the residents economic independence resilience (−0.398) and traditional knowledge resilience (−0.422). It can be seen that urban areas rely more on the resilience of the socio-economic structure, while rural areas are more dependent on their own knowledge and economic independence. This result can be used as a reference for developing strategies to improve urban and rural resilience. |
format | Online Article Text |
id | pubmed-9331052 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93310522022-07-29 A Comparative Study of the Resilience of Urban and Rural Areas under Climate Change Su, Qingmu Chang, Hsueh-Sheng Pai, Shin-En Int J Environ Res Public Health Article The impact of climate change in recent years has caused considerable risks to both urban and rural systems. How to mitigate the damage caused by extreme weather events has attracted much attention from countries in recent years. However, most of the previous studies on resilience focused on either urban areas or rural areas, and failed to clearly identify the difference between urban and rural resilience. In fact, the exploration of the difference between the resilience characteristics of cities and villages under climate change can help to improve the planning strategy and the allocation of resources. In this study, the indicators of resilience were firstly built through a literature review, and then a Principal Component Analysis was conducted to construct an evaluation system involving indicators such as “greenland resilience”, “community age structure resilience”, “traditional knowledge resilience”, “infrastructure resilience” and “residents economic independence resilience”. Then the analysis of Local Indicators of Spatial Association showed some resilience abilities are concentrated in either urban or rural. Binary logistic regression was performed, and the results showed urban areas have more prominent abilities in infrastructure resilience (the coefficient value is 1.339), community age structure resilience (0.694), and greenland resilience (0.3), while rural areas are more prominent in terms of the residents economic independence resilience (−0.398) and traditional knowledge resilience (−0.422). It can be seen that urban areas rely more on the resilience of the socio-economic structure, while rural areas are more dependent on their own knowledge and economic independence. This result can be used as a reference for developing strategies to improve urban and rural resilience. MDPI 2022-07-22 /pmc/articles/PMC9331052/ /pubmed/35897290 http://dx.doi.org/10.3390/ijerph19158911 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Su, Qingmu Chang, Hsueh-Sheng Pai, Shin-En A Comparative Study of the Resilience of Urban and Rural Areas under Climate Change |
title | A Comparative Study of the Resilience of Urban and Rural Areas under Climate Change |
title_full | A Comparative Study of the Resilience of Urban and Rural Areas under Climate Change |
title_fullStr | A Comparative Study of the Resilience of Urban and Rural Areas under Climate Change |
title_full_unstemmed | A Comparative Study of the Resilience of Urban and Rural Areas under Climate Change |
title_short | A Comparative Study of the Resilience of Urban and Rural Areas under Climate Change |
title_sort | comparative study of the resilience of urban and rural areas under climate change |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9331052/ https://www.ncbi.nlm.nih.gov/pubmed/35897290 http://dx.doi.org/10.3390/ijerph19158911 |
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