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

Big Earth Data 2022年第1期6卷 3-17页

作者： Li Wang Yuanhuizi He Yuelin Zhang Lei Wang Huicong Jia Quan Zhou Bo Yu Meimei Zhang Zhengyang Lin Fang Chen State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina University of Chinese Academy of Sciences BeijingChina Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina

In this study,based on the EM-DAT(The Emergency Events Database)database,disaster assessment for the“Belt and Road”region 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 *** addition,using the data available in the EM-DAT,an overview of disaster records is used to quantify disasters for a total of 73 *** 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 *** 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.

关键词： EM-DAT database the Belt and Road region Sustainable Development Goals sdg13.1.1 indicator disaster risk reduction

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