Collaborative Research: Measuring Social Vulnerability - Reducing Uncertainty and Validating Indicators

合作研究：衡量社会脆弱性——减少不确定性并验证指标

• 批准号: 1333243
• 负责人: Christopher Emrich
• 金额: $ 17.4万
• 依托单位: University of South Carolina at Columbia
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-15 至 2017-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1333243&HistoricalAwards=false
• 关键词: Collaborative; Research; Measuring; Social; Vulnerability

The objective of this collaborative research study is to improve the reliability of social vulnerability indicators by reducing uncertainties in input data and methods, and validating output metrics. Social vulnerability has been receiving increasing attention by disaster planners at local, state, and federal levels as they seek to reduce adverse impacts of natural hazards. Yet far too little is currently understood about the robustness of the leading vulnerability indicators, both in terms of the approaches used to build them and their ability to adequately represent real world conditions. There is a critical need for methodological advancements to improve the precision and accuracy of social vulnerability indicators. Without such advancements, the use of social vulnerability indicators in disaster mitigation, preparedness, and recovery could mislead decision-making. Based on a study area of the Southeast U.S., the project will develop novel regionalization routines and apply global sensitivity analysis and multiple regression to census data inputs and output vulnerability indicators. The research is expected to generate new understanding of the critical inputs and decision points in social vulnerability modeling, the level of agreement of resultant indicators with observed disaster outcomes, and the influence of uncertainty in social vulnerability modeling. By narrowing the existing gap between vulnerability models and real-world practice, improved social vulnerability indicators will allow for better disaster planning and interventions that account for the most vulnerable populations.The project has great potential to transform dominant approaches for the measurement of social vulnerability to hazards. The finalized methodology will be made widely accessible to both researchers and the public through an internet-GIS application that generates user-customizable vulnerability indices. The improved vulnerability metrics will also be shared with state and federal disaster planners through existing relationships with the research team. The study contributes to training the next generation of hazards researchers through the direct involvement of graduate and undergraduate students, including those from groups historically underrepresented in graduate research and education. The project findings will be integrated into the classroom through the development of learning modules for existing courses that explore urban geography and interactions between hazards and society.

这项合作研究的目的是通过减少输入数据和方法的不确定性并验证输出指标来提高社会脆弱性指标的可靠性。 在寻求减少自然灾害的不利影响时，社会脆弱性越来越受到地方、州和联邦各级灾害规划者的关注。 然而，目前人们对主要脆弱性指标的稳健性了解甚少，无论是在构建这些指标的方法还是其充分代表现实世界条件的能力方面。 迫切需要改进方法来提高社会脆弱性指标的精确度和准确性。 如果没有这些进步，在减灾、备灾和恢复中使用社会脆弱性指标可能会误导决策。 该项目将基于美国东南部的一个研究区域，开发新颖的区域化程序，并将全球敏感性分析和多元回归应用于人口普查数据输入和输出脆弱性指标。 该研究预计将对社会脆弱性建模中的关键输入和决策点、所得指标与观察到的灾害结果的一致性程度以及社会脆弱性建模中不确定性的影响产生新的理解。 通过缩小脆弱性模型与现实世界实践之间的现有差距，改进的社会脆弱性指标将有助于更好地考虑最脆弱人群的灾害规划和干预措施。该项目具有改变衡量社会灾害脆弱性的主要方法的巨大潜力。 最终确定的方法将通过生成用户可定制漏洞指数的互联网地理信息系统应用程序向研究人员和公众广泛开放。 改进后的脆弱性指标还将通过与研究团队的现有关系与州和联邦灾难规划者共享。 该研究通过研究生和本科生的直接参与，有助于培训下一代灾害研究人员，包括来自历史上在研究生研究和教育中代表性不足的群体的学生。 该项目的研究结果将通过为现有课程开发学习模块来融入课堂，这些课程探索城市地理以及灾害与社会之间的相互作用。