Fusion of Terrain Information and Mobile Phone Location Data for Flood Area Detection in Rural Areas

Abstract

Recently, the frequency and intensity of weather-related disasters are increasing and are becoming more ubiquitous, often devastating vulnerable rural areas. To prepare for speedy and effective first response, we need a flood detection method that works much faster and is able to cover a wider area compared to conventional methods that use CCTV cameras and low cost sensors, which are costly to distribute ubiquitously in all areas with possible flood threats. With the spread of mobile phones, we are able to obtain real time anonymized location information of individuals in a ubiquitous, low cost, and a continuous manner from users that have agreed to provide their location data for disaster relief purposes. Here we propose a novel method that infers flooded areas in real time by detecting anomalous behaviors of individuals using mobile phone location data. We are motivated in applying our method to rural areas that are costly to cover using cameras and sensors. To overcome the sparseness of mobile phone location signals in such rural areas, our method combines mobile phone location data with terrain information including the digital elevation model and river trajectory data. We evaluated our method using real world data from 2 severe floods in the rural parts of Japan and verified that our method is more accurate and has numerous advantages compared to conventional methods. This work presents the potential use of mobile phone data as a complementary, if not an alternative method for flood detection especially in rural areas.