Open AccessDetecting Damaged Regions after Natural Disasters using Mobile Phone Data: The Case of Ecuador
Author(s) -
María-Belén Guaranda,
Galo Castillo-López,
Fabricio Layedra,
Carmen Vaca
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.52591/lxai202012125
Subject(s) - epicenter , mobile phone , classifier (uml) , computer science , natural disaster , phone , mobile telephony , data mining , geography , artificial intelligence , geology , seismology , telecommunications , mobile radio , meteorology , linguistics , philosophy
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.