Estimating Population Risk for Coastal Disasters Using Spatial Models with Global Data

Coastal areas present high risk in case of tsunami, hurricanes or floods due to the higher population densities. Traditional physical models or risk maps provide limited help since disaster spatial extent can not be available immediately for the emergency management. This impairs postdisaster response; more fatalities can be expected due to the uneven distribution of medical supplies, food or equipment. Geographic Information Systems analysis with global datasets on terrain and population provides new venue for the post-disaster response in the form of immediate (within 24 – 96 hours) model of affected population and geographical extent of disaster. Presented case study shows such example for the Northern Sumatra affected by tsunami of 2004. The results of presented modeling were compared with population data collected from the posttsunami field survey. Obtained regression is statistically meaningful (R2 =0.58) and indicates that presented methodology can be a useful tool during the post-disaster management.