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Documentation for the U.S. Social Vulnerability Index, v1 (2000, 2010, 2014, 2016, 2018)

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Mendeley Data2024-03-27 更新2024-06-28 收录
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https://beta.sedac.ciesin.columbia.edu/data/set/usgrid-us-social-vulnerability-index/docs
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The U.S. Social Vulnerability Index Grids data set contains gridded layers for the overall Centers for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI) using four sub-category themes (Socioeconomic, Household Composition & Disability, Minority Status & Language, and Housing Type & Transportation) based on census tract level inputs from 15 variables for the years 2000, 2010, 2014, 2016, and 2018. SVI values range between 0 and 1 based on their percentile position among all census tracts in the U.S., with 0 representing lowest vulnerability census tracts and 1 representing highest vulnerability census tracts. SEDAC has gridded these vector inputs to create 1 km spatial resolution raster surfaces allowing users to obtain vulnerability metrics for any user defined area within the U.S. Utilizing inputs from CIESIN's Gridded Population of the World, Version 4 (GPWv4) Revision 11 data sets, a mask is applied for water, and optionally, for no population. The data are provided in two different projection formats, NAD83 as a U.S. specific standard, and WGS84 as a global standard. The goal of the SVI is to help identify vulnerable communities by ranking them on these inputs across the U.S.

美国社会脆弱性指数网格数据集包含美国疾病控制与预防中心(Centers for Disease Control and Prevention, CDC)社会脆弱性指数(Social Vulnerability Index, SVI)的网格化图层,该指数基于四大类子主题构建:社会经济、家庭构成与残疾、少数群体地位与语言,以及住房类型与交通,其输入来源为2000、2010、2014、2016及2018年共15项变量的普查分区级数据。SVI的取值范围为0至1,该取值基于全美所有普查分区中的百分位排名:0代表脆弱性最低的普查分区,1代表脆弱性最高的普查分区。社会经济数据与应用中心(Socioeconomic Data and Applications Center, SEDAC)将上述矢量输入数据进行网格化处理,生成空间分辨率为1公里的栅格表面,支持用户获取美国境内任意自定义区域的脆弱性指标。本数据集依托国际地球科学信息网络中心(Center for International Earth Science Information Network, CIESIN)的《世界网格化人口第4版修订版11》(Gridded Population of the World, Version 4 (GPWv4) Revision 11)数据集作为输入,已应用水体掩膜,且可选择应用无人口区域掩膜。数据集提供两种投影格式:美国本土标准NAD83与全球标准WGS84。SVI的设计目标是通过全美范围内基于上述输入变量的排名,协助识别脆弱社区。
创建时间:
2023-06-28
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