In recent years, the ever-changing climate has caused natural disasters in various countries to occur frequently. Climate change has become one of the factors that have caused this country to be vulnerable. This article mainly quantitatively studies how climate change affects regional instability. A comprehensive indicator evaluation method is used to establish a PSA model. The country's vulnerability is defined in terms of the dimensions of pressure, sensitivity, and adaptive capability. This article selected Philippines as the research object, and based on the data processing by PSA model, we obtained the Fragile State Index (FSI) of Philippines in the past ten years. It has found that the flooding in 2012 has made it more vulnerable to Philippines and the results of the analysis are in line with the actual situation. Then, the K-means clustering algorithm is used to get a tipping point (0.5) that can define whether it is fragile or not. What's more, the critical point is verified to be reasonable. Finally, under the guidance of the data of the three dimensions and first-class indicators, the intervention measures that the country should take to address climate change are proposed to reduce regional instability.
| Published in | American Journal of Civil Engineering (Volume 6, Issue 3) |
| DOI | 10.11648/j.ajce.20180603.13 |
| Page(s) | 99-108 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2018. Published by Science Publishing Group |
Climate Change, Regional Instability, Fragile State Index, PSA Model
| [1] | Füesel H M. Vulnerability:ageneraly applicable conceptual framework for climate change research[J]. Global Environmental Change, 2007, 17 (2):155-167. |
| [2] | Moss R H, Brenkert A L, Malone E L. Vulnerability to cli- mate change: A quantitative approach [J]. Advances in Sci- ence and Research, 2001 (1): 1-88. |
| [3] | Klein R J T, Nichols R J. Asesment of coastal vulnerability to climate change [J]. Ambio, 1999, 28 (2):182-187. |
| [4] | Tan Shuhao, Tan Wenlie, Li Qingting, Li Tingyu, Zhu Yong, Zhang Qiaoyun, Liu Bo. Analysis of herdsmen's social vulnerability under the pressure of climate change——Based on the investigation of 4 animal husbandry flags in Xilinguole League of Inner Mongolia[J]. Chinese Countryside Economy. 2016 (07). |
| [5] | Xu Tingting, Xu Changle, Liu Yang. Research on the Evaluation of Social and Economic Vulnerability of Shanghai under the Background of Global Climate Change——Based on PSR Model[J]. Resource Development and Market. 2015 (03). |
| [6] | Feng Chunyan. Study on Social Vulnerability of Drought Disaster in Shandong Province[D]. Qufu Normal University. 2017. |
| [7] | Qiao Mengmeng. Study on Water Resources Vulnerability in Suzhou City[D]. Suzhou University of Science and Technology. 2017. |
| [8] | Niemeijer, D. Developing Indicators for Environmental Policy: Data-driven and Theory-driven Approaches Examined by Example[J]. Environmental Science & Policy, 5 (2): 91-103, 2002. |
| [9] | IPCC. Climate Change 2007—The Physical Science Basis: Working Group I Contribution to the Fourth Assessment Report of the IPCC [M]. Cambridge University Press, 2007. |
| [10] | Chen Ping, Chen Xiaoling. A Review of the Research on the Vulnerability of Human-environment Coupling System under Global Environmental Change [J]. Progress in Geography. 2010 (04). |
| [11] | Mccarthy, J. J.; Canziani, O. F.; Leary, N. A.; Dokken, D. J. and White, K. S. (eds.). Climate Change 2001: Impacts, Adaptation, and Vulnerability: Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Chang [M]. Cambridge University Press, 2001. |
| [12] | Sun Pingjun, Xiu Chunliang. Study on the vulnerability of mining cities' economic development based on PSE model [J]. Geographical Research. 2011 (02). |
| [13] | Wang Yue, Tian Shen, Zhao Qiping, Li Xudong. Research Progress on Adaptability of High-Temperature Heat Wave Weather Based on Vulnerability [J]. Journal of Environment and Health. 2017 (03). |
APA Style
Hui Liao, Kunling Han, Shuo Sun, Yajing Jin. (2018). The Evaluation of Regional Instability to Climate Change Based on the PSA Model—A Case Study of Philippines. American Journal of Civil Engineering, 6(3), 99-108. https://doi.org/10.11648/j.ajce.20180603.13
ACS Style
Hui Liao; Kunling Han; Shuo Sun; Yajing Jin. The Evaluation of Regional Instability to Climate Change Based on the PSA Model—A Case Study of Philippines. Am. J. Civ. Eng. 2018, 6(3), 99-108. doi: 10.11648/j.ajce.20180603.13
AMA Style
Hui Liao, Kunling Han, Shuo Sun, Yajing Jin. The Evaluation of Regional Instability to Climate Change Based on the PSA Model—A Case Study of Philippines. Am J Civ Eng. 2018;6(3):99-108. doi: 10.11648/j.ajce.20180603.13
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Download@article{10.11648/j.ajce.20180603.13,
author = {Hui Liao and Kunling Han and Shuo Sun and Yajing Jin},
title = {The Evaluation of Regional Instability to Climate Change Based on the PSA Model—A Case Study of Philippines},
journal = {American Journal of Civil Engineering},
volume = {6},
number = {3},
pages = {99-108},
doi = {10.11648/j.ajce.20180603.13},
url = {https://doi.org/10.11648/j.ajce.20180603.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajce.20180603.13},
abstract = {In recent years, the ever-changing climate has caused natural disasters in various countries to occur frequently. Climate change has become one of the factors that have caused this country to be vulnerable. This article mainly quantitatively studies how climate change affects regional instability. A comprehensive indicator evaluation method is used to establish a PSA model. The country's vulnerability is defined in terms of the dimensions of pressure, sensitivity, and adaptive capability. This article selected Philippines as the research object, and based on the data processing by PSA model, we obtained the Fragile State Index (FSI) of Philippines in the past ten years. It has found that the flooding in 2012 has made it more vulnerable to Philippines and the results of the analysis are in line with the actual situation. Then, the K-means clustering algorithm is used to get a tipping point (0.5) that can define whether it is fragile or not. What's more, the critical point is verified to be reasonable. Finally, under the guidance of the data of the three dimensions and first-class indicators, the intervention measures that the country should take to address climate change are proposed to reduce regional instability.},
year = {2018}
}
TY - JOUR T1 - The Evaluation of Regional Instability to Climate Change Based on the PSA Model—A Case Study of Philippines AU - Hui Liao AU - Kunling Han AU - Shuo Sun AU - Yajing Jin Y1 - 2018/06/27 PY - 2018 N1 - https://doi.org/10.11648/j.ajce.20180603.13 DO - 10.11648/j.ajce.20180603.13 T2 - American Journal of Civil Engineering JF - American Journal of Civil Engineering JO - American Journal of Civil Engineering SP - 99 EP - 108 PB - Science Publishing Group SN - 2330-8737 UR - https://doi.org/10.11648/j.ajce.20180603.13 AB - In recent years, the ever-changing climate has caused natural disasters in various countries to occur frequently. Climate change has become one of the factors that have caused this country to be vulnerable. This article mainly quantitatively studies how climate change affects regional instability. A comprehensive indicator evaluation method is used to establish a PSA model. The country's vulnerability is defined in terms of the dimensions of pressure, sensitivity, and adaptive capability. This article selected Philippines as the research object, and based on the data processing by PSA model, we obtained the Fragile State Index (FSI) of Philippines in the past ten years. It has found that the flooding in 2012 has made it more vulnerable to Philippines and the results of the analysis are in line with the actual situation. Then, the K-means clustering algorithm is used to get a tipping point (0.5) that can define whether it is fragile or not. What's more, the critical point is verified to be reasonable. Finally, under the guidance of the data of the three dimensions and first-class indicators, the intervention measures that the country should take to address climate change are proposed to reduce regional instability. VL - 6 IS - 3 ER -
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