| 2022年贵州省自然灾害灾情时空特征分析 |
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| 引用本文： | 许启松. 2022年贵州省自然灾害灾情时空特征分析[J]. 贵州地质, 2024, 0(1): 75-79, 17 |
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| 作者姓名： | 许启松 |
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| 作者单位： | 1.贵州省应急管理厅,贵州贵阳550001;2.贵州省减灾中心,贵州贵阳550001 |
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| 基金项目： | 贵州省暴雨-地质灾害链典型区综合风险与减灾能力调查评估与防范技术业务应用示范、多灾种重大自然灾害综合风险评估与防范技术集成平台及示范(2018YFC1508806);贵州省综合防灾减灾(一期)数据库及贵阳市地震灾情信息管理平台建设(黔科合SY字〔2014〕3064号)。 |
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| 摘 要： | 本文基于贵州省2022年年度灾情数据,采用自然断点(Natural Breaks)空间数据分类分级方法加权标准化灾情指数(Weighted Standardized Disaster Index,WSDI),基于加权标准化灾情指数和4个维度指数对贵州省受灾情况进行了分类分级,并对贵州省自然灾害分布和变化趋势情况进行了分析。从空间分布来看,贵州省2022年自然灾害分布总体呈北部重、中部轻的规律;从灾害类型来看,洪涝、干旱两种灾害影响最为严重;从灾害时间分布来看,6、7两月灾情最重。
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| 关 键 词： | 自然灾害 加权标准化灾情指数 灾害损失时空特征 灾害分布趋势 |
| 收稿时间： | 2023-09-06 |
Analysis on the Spatial-temporal Distribution Characteristics of Natural Disasters in Guizhou Province in 2022 |
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| XU Qi-song. Analysis on the Spatial-temporal Distribution Characteristics of Natural Disasters in Guizhou Province in 2022[J]. Guizhou Geology, 2024, 0(1): 75-79, 17 |
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| Authors: | XU Qi-song |
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| Affiliation: | 1.Department of Emergency Management of Guizhou Province,Guiyang 550001,Guizhou,China;2.Disaster Reduction Center of Guizhou Province,Guiyang 550001,Guizhou,China |
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| Abstract: | Based on the annual Disaster data of Guizhou Province in 2022,in this paper, it used the Natural Breaks spatial data classification and grading method and the Weighted Standardized Disaster Index(WSDI)Based on the weighted standardized disaster situation index and four dimensional index,the disaster situation in Guizhou Province was classified and graded,and the distribution and change trend of natural disasters in Guizhou province were analyzedFrom the perspective of spatial distribution,the distribution of natural disasters in Guizhou Province in 2022 is generally heavier in the north and lighter in the middleFrom the perspective of disaster types,flood and drought have the most serious impactFrom the distribution of disaster time,June and July were the most severe |
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| Keywords: | Natural disasters Weighted standardized disaster index Spatial and temporal characteristics of disaster loss Disaster distribution trend |
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