Regresar

RiSC: Quantifying change after natural disasters to estimate infrastructure damage with mobile phone data

Abstract:

Natural disasters have proven that governments, even in developed countries, have difficulties to get up-to-date data about not only affected people but also the location and intensity of infrastructure damage when a country is shook by the nature. Therefore, knowing how mobility patterns are changing, in the post disaster time-frame, is crucial in order to settle rescue centers and send help to the most affected areas. In this scenario, we analyze the relations between human mobility patterns and the effects of an earthquake that shook Ecuador on April 16th, 2016. We do so using more than 11 millions of aggregated call detail records provided by Telefonica. We propose a metric named Reach Score to build timeseries as a way to characterize the residents geographic reach according to their mobile activity. Next, we define the metric Reach Score change, RiSC to capture differences in mobility among two given dates. Our results show that these two metrics calculated on data from the day before and the day after the disaster reflect both the overall change in mobility at the province level and the intensity of infrastructure damage at canton level. In fact, we obtain a Pearson correlation coefficient of r = -0.819 between the metric RiSC and the infrastructure damage score taken from official data.