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文献详情 >Disaster assessment for the“Be... 收藏

Disaster assessment for the“Belt and Road”region based on SDG landmarks

作     者:Li Wang Yuanhuizi He Yuelin Zhang Lei Wang Huicong Jia Quan Zhou Bo Yu Meimei Zhang Zhengyang Lin Fang Chen 

作者机构:State Key Laboratory of Remote Sensing ScienceAerospace Information Research InstituteChinese Academy of SciencesBeijingChina University of Chinese Academy of SciencesBeijingChina Key Laboratory of Digital Earth ScienceAerospace Information Research InstituteChinese Academy of SciencesBeijingChina 

出 版 物:《Big Earth Data》 (地球大数据(英文))

年 卷 期:2022年第6卷第1期

页      面:3-17页

核心收录:

学科分类:083002[工学-环境工程] 0830[工学-环境科学与工程(可授工学、理学、农学学位)] 0709[理学-地质学] 08[工学] 0708[理学-地球物理学] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

基  金:supported by the Strategic Priority Research Program of the Chinese Academy of Sciences under grant no.XDA19030404. 

主  题:EM-DAT database the Belt and Road region Sustainable Development Goals SDG13.1.1 indicator disaster risk reduction 

摘      要:In this study,based on the EM-DAT(The Emergency Events Database)database,disaster assessment for the“Belt and Roadregion was carried out in relation to the SDG_(13.1.1)indicator of the Sustainable Development Goals(SDGs)agenda launched in 2015.A new method for diagnosing trends in the SDG_(13.1.1)indicators based on the Theil-Sen median method is proposed.In addition,using the data available in the EM-DAT,an overview of disaster records is used to quantify disasters for a total of 73 countries.The disaster trends for the period 2015‒2019 were found to demon-strate the following.(1)As a result of geological and climate con-ditions,Asia and Africa are high-risk disaster areas and disasters have caused considerable economic losses and affected the popu-lations in developing and underdeveloped countries in these regions.(2)The clear positive value ofΔs_(13.1.1)found for China reflects the country’s encouraging achievements in disaster preven-tion and mitigation.(3)The value of SDG_(13.1.1)was observed to be increasing in South Asia,northwest Africa and South Africa,with the increase in India and Mauritania being the most serious.The new method proposed in this paper allows the real trend in the SDG_(13.1.1)indicator in various countries to be derived and provides critical intelligence support for international disaster risk reduction plans and sustainable development goals.

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