Authors: Joseph Holler*, Middlebury College
Topics: Hazards and Vulnerability, Geographic Information Science and Systems
Keywords: vulnerability index, crowd-sourced data, model validation, Hurricane Harvey
Session Type: Paper
Start / End Time: 8:00 AM / 9:40 AM
Room: Napoleon D1, Sheraton 3rd Floor
Presentation File: No File Uploaded
Social vulnerability indices describe the likelihood that a region's exposure to natural hazard will result in harm to the people in that region. The indices are constructed with recent aggregate socio-economic data to predict potential harm in the future, and their methodology is based on vulnerability and hazards theory and empirical evidence of past disasters. Indices can inform disaster risk reduction, optimize disaster response and recovery, and evaluate disaster management. For reliable use in policy, indices should be externally validated with evidence of harm from hazard exposure. However, external validation has proven to be a challenging research problem because hazard exposures and impacts are heterogeneous; and general social vulnerability indices translate imperfectly to the specific geographies, hazard types, timing, and phases of disasters.
Hurricane Harvey provides a unique opportunity to externally validate vulnerability indices. Facing an overburdened 911 emergency network, residents of the greater Houston area turned to posting pleas for emergency evacuation with explicit location descriptions on social media. Volunteers of HarveyRELIEF in turn monitored social media and coordinated emergency requests for rescue with a database and dynamic map. By HarveyRELIEF’s own estimation, they processed 10,120 reports to evacuate 29,641 people. We consider such pleas for evacuation as evidence of “harm” and use them to externally validate two social vulnerability indices. We then propose techniques to apply crowd-sourced data and general indices to the specific geography, time, hazard type, and phase of a hazard disaster event.