Global Volcano Total Economic Loss Risk Deciles
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https://www.earthdata.nasa.gov/data/catalog/sedac-ciesin-chrr-ndh-volcano-telrd-1.00
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Global Volcano Total Economic Loss Risk Deciles is a 2.5 minute grid of global volcano total economic loss risks. First, subnational distributions of Gross Domestic Product (GDP) are computed using a two-fold process. Where applicable, the proportional contribution of subnational Units are determined following the methodology of Sachs et al. (2003) and these proportions are used against World Bank Development Indicators to determine a GDP value for the subnational Unit. Once a national GDP has been spatially stratified into the smallest administrative Units available, it is further distributed based upon Gridded Population of the World, Version 3 (GPWv3) population distributions. A per capita contribution value is determined for each Unit, and this value is multiplied by the population per grid cell. Once the GDP has been determined on a per grid cell basis, then the spatially variable loss rate as derived from EM-DAT historical records is used to determine the total economic loss posed to a grid cell by volcano hazards. The final surface does not present absolute values of total economic loss, but rather a relative decile (1-10) ranking of grid cells based upon the calculated economic loss risks. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
全球火山总经济损失风险十进制数据集系一幅2.5分钟网格的全球火山总经济损失风险图。首先,通过双重过程计算国民生产总值(GDP)的次国家级分布。在适用的情况下,参照Sachs等(2003)的方法确定次国家级单位的贡献比例,并以此比例对照世界银行发展指标,为次国家级单位确定GDP值。一旦国家GDP被空间分层至最小的行政单元,便进一步基于世界人口网格分布版3(GPWv3)的人口分布进行分配。为每个单元确定人均贡献值,并将其与每个网格单元的人口相乘。在确定每个网格单元的GDP后,接着使用源自EM-DAT历史记录的空间变量损失率来确定火山灾害对网格单元造成的总经济损失。最终表面不展示总经济损失的绝对值,而是基于计算出的经济损失风险,对网格单元进行相对十进制(1-10)的排名。此数据集是哥伦比亚大学灾害与风险评估研究中心(CHRR)、国际重建与发展银行/世界银行以及哥伦比亚大学国际地球科学信息网络中心(CIESIN)合作的结果。
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Earthdata



