Returning Home Strategy Analysis Using Mobile Sensing Data in Tohoku Earthquake

In recent decades, there has been a significant increase in the frequency and intensity of natural disasters. Such catastrophic events often result in large-scale population movements and evacuations. Analyzing these human activities is crucial for effective planning of disaster control, and ensuring long-term social stability. While some research has been conducted on post-disaster analysis, particularly focusing on big earthquakes [15, 22], very few studies have taken into account the influence of personal factors on decision-making. Understanding the key factors that drive individuals to choose a strategy, such as returning home, after a big earthquake is essential for comprehending human decision-making in such situations. Additionally, a considerable number of people may remain in companies or shelters due to the disruption of transportation networks. However, conducting such research is challenging due to the lack of big human mobility data. Furthermore, identifying the key factors that individuals consider when making decisions to return home after a big disaster is critical. To address these challenges, this study utilizes smartphone location data to track people’s movements. A large and diverse dataset was collected during the Tohoku earthquake in Japan in 2011, allowing for the discovery of grid-based regions with different functions based on POI distributions in a region. The analysis conducted in this study aims to explore the fundamental laws governing human mobility following disasters. This paper is an extended version of our previous lightning talks [24].