Abstract
Information is a critical resource in disaster response scenarios. Data regarding the geographic extent, severity, and socioeconomic impacts of a disaster event can help guide emergency responders and relief operations, particularly when delivered within hours of data acquisition. Information from remote observations provides a valuable tool for assessing conditions ‘on the ground’ more quickly and efficiently. Here, we evaluate the social value of a near real-time flood impact system using a disaster response case study, and quantify the Value of Information (VOI) of satellite-based observations for rapid response using a hypothetical flooding disaster in Bangkok, Thailand. MODIS imagery from NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) system is used to produce operational estimates of inundation depths and economic damages. These rapid Earth observations are coupled with a decision-analytical model to inform decisions on emergency vehicle routing. Emergency response times from vehicles routed using flood damage data are compared with baseline routes without the benefit of advance information on road conditions. Our results illustrate how the application of near real-time Earth observations can improve the response time and reduce potential encounters with flood hazards when compared with baseline routing strategies. Results indicate a potential significant economic benefit (i.e. millions of dollars) from applying near real-time Earth observations for improved flood disaster response and management.
Highlights
Natural disasters like floods can have devastating societal impacts
Emergency response vehicles stationed at dispatch centers are routed to each of the population sites and their response times and navigation details are evaluated in the presence and absence of information on flood conditions
The disaster response scenario described in this study represents a theoretical example of how near real-time (NRT) Earth observations can potentially be used to inform a disaster management decision
Summary
Direct damages from flooding, such as the loss of human life or the destruction of infrastructure have immediate social ramifications, while indirect impacts like reduced business production or loss of income can lead to more protracted socioeconomic effects (Haraguchi and Lall, 2015). This is especially true in regions like the Lower Mekong River Basin (LMRB), where its combination of high population density, seasonal monsoons, and low-lying topography make it susceptible to flooding (Gale and Saunders, 2013) (Figure 1a). We extend the VOI concept to a flood-related disaster management scenario
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