地理编码在社会科学中改善地震预警的应用

Danielle Sumy
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引用次数: 1

摘要

地理编码是一种空间分析方法,它使用地址信息(如街道地址、十字路口、人口普查区、邮政编码等)来确定地理坐标(纬度和经度)。近几十年来,地理编码已经超越了其用于人口普查和人口统计信息的主要用途,在减少灾害风险,甚至地震预警方面有了新的应用。在这里,我展示了地理编码技术对地震预警系统的有用性,并将其应用于依赖于调查响应数据和众包视频片段的案例研究。收集这些数据集最初是为了了解在美国西海岸地震预警系统ShakeAlert®上进行的测试的有效性,以及人们在地震期间的行为。对这些数据进行地理编码可以提高我们对系统的整体技术理解,展示个人是否采取了“蹲下、掩护和坚持”等保护措施,并突出系统正在达到或无意中遗漏的社区人口统计数据。这些社会科学数据集与地理编码信息的结合加深了我们对这些基本以人为中心的系统的认识,包括如何为具有访问权限和功能需求的人和个人改善警报的分发。将来,这项工作可能有助于验证美国地质调查局的“你感觉到了吗?”的响应和地震烈度,特别是在地震台网稀疏的地区。
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Geocoding Applications for Social Science to Improve Earthquake Early Warning
Geocoding is a spatial analysis method that uses address information (e.g., street address, intersection, census tract, zip code, etc.) to determine geographical coordinates (latitude and longitude). In recent decades, geocoding has gone beyond its primary use for census and demographic information to novel applications in disaster risk reduction, even to earthquake early warning. Here I demonstrate the usefulness of geocoding techniques to earthquake early warning systems as applied to case studies that relied on survey response data and crowd-sourced video footage. These datasets were initially collected to understand the efficacy of tests conducted on ShakeAlert®, the earthquake early warning system for the West Coast of the United States, and how people behave during earthquakes, respectively. Geocoding these data can improve our overall technical understanding of the system, demonstrate whether individuals take protective actions such as ‘Drop, Cover, and Hold On’, and spotlight community demographics that the system is reaching or unintentionally missing. The combination of these social science datasets with geocoding information deepens our knowledge of these fundamentally human-centered systems, including how to improve the distribution of alerts for people and individuals with access and functional needs. In the future, this work may help verify U.S. Geological Survey ‘Did You Feel It?’ responses and seismic intensity, especially in regions with sparse seismic networks.
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