利用移动电话数据在自然灾害后检测受损地区:厄瓜多尔的案例

LatinX in AI at Neural Information Processing Systems Conference 2020 Pub Date : 2020-12-12 DOI:10.52591/lxai202012125

Maria-Belen Guaranda, Galo Castillo-López, Fabricio Layedra, Carmen Vaca

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引用次数: 0

摘要

在这项工作中，我们使用手机活动数据来推断2016年地震后厄瓜多尔Manabí省的受影响区域，震中在同一省。我们计算了一系列的特征来训练一个基于k近邻算法的分类器，以75%的精度检测受影响的区域。我们将我们的结果与灾难发生两个月后发布的官方报告进行比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Detecting Damaged Regions after Natural Disasters using Mobile Phone Data: The Case of Ecuador

In this work, we use mobile phone activity data to infer the affected zones in the Ecuadorian province of Manabí, after the 2016 earthquake, with epicenter in the same province. We calculate a series of features to train a classifier based on the K-Nearest Neighbors algorithm to detect affected zones with a 75% of precision. We compare our results with official reports published two months after the disaster.

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LatinX in AI at Neural Information Processing Systems Conference 2020

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