Natural Hazards, Risk Analysis and Emergency Preparedness: Applying Spatial Methods in Disaster Risk Management APPLYING SPATIAL METHODS IN DISASTER RISK MANAGEMENT

Abstract

Losses from natural hazards have been increasing steadily over the last decades. Yet, tools exist that can reduce risks to disasters and prevent hazards from turning into disasters. This study is intended to contribute to a reversal of the staggering economic losses by advancing the application of Geographic Information Systems (GIS) in the field of disaster risk management. Organized as a series of papers for publication, the dissertation first sets the stage by presenting a case study on Louisiana and its vulnerability to hurricanes. Thereafter, it examines and contributes to two fields that have proven to save lives and lower damages following catastrophes: emergency preparedness and risk assessments. Emergency preparedness, through contingency planning, disaster prediction, and early warning, is critical to reduce disaster impacts. While GIS is increasingly recognized as a key ingredient for successful emergency preparedness, systematic knowledge about how to best use GIS is still in its infancy. This dissertation investigates the status quo of the use of GIS in emergency preparedness and offers recommendations for moving ahead. Based on interviews with emergency responders from three different U.S. states, the bottlenecks and the successes of the use of GIS in the emergency response to Hurricane Katrina are examined. Risk assessments are tools to identify and understand risk. Given the high loss potential in urban areas, surprisingly little is known about the risk of cities. Oddly, a comprehensive ranking of cities’ risk has been lacking. This research addresses this gap by developing, for the first time, a disaster risk ranking of the world’s major cities. The ranking measures mortality and economic risks to major natural hazards for the 1,943 main cities in 110 countries. Building on these efforts, the most recent scientific and demographic information is applied in order to estimate the future impacts of climate change on storm surges that will strike coastal urban populations.