Assessing dynamics of human vulnerability at community level – Using mobility data

Abstract

The comprehension of the community vulnerability levels is pivotal for understanding how communities respond to diverse hazard events and supporting community resilience management. Existing assessment approaches often treat social vulnerability as static by assuming that residents stay within their home community, which ignored the influence of human mobilities on the vulnerability distribution. To overcome these limitations, in this study, we developed a spatial-temporal community vulnerability assessment framework that integrates human mobility with demographic characteristics. Specifically, we integrated geographic data, e.g., mobile phone data, and human activity trajectory data, e.g., activity survey data, to (1) map demographic-dependent varying human trajectory, (2) identify the dynamic distributions of social vulnerable groups, and (3) based on this to more comprehensively evaluate community vulnerability. We selected Philadelphia County of Pennsylvania as a case study to validate this method. The simulation results demonstrate that the spatial-temporal distribution of some vulnerable populations undergoes significant changes over time due to individual mobility. Furthermore, we also find that different vulnerable groups within the same community show various mobility patterns. Our results highlight the importance of integrating demographic-based human mobility into community vulnerability assessment and complementing current static vulnerability with a more comprehensive understanding to support emergency management, which could enhance the effectiveness and efficiency of timely emergency planning and responses to disasters.