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Satellite remote sensing in disaster relief: FY23 HADR Technical Investment Program(9.12 MB)

Summary

Disasters annually cost the U.S. billions of dollars in direct costs and economic loss. In particular, the increasing frequency and intensity of natural hazard incidents, such as hurricanes, tornadoes, floods, and wildfires, strains the nation's emergency management enterprise. Knowing that the current approach to emergency management is unsustainable, practitioners and policy makers look to use new tools and technologies to mitigate, prepare for, respond to, and recover from disasters. One of those technologies is satellite remote sensing. As persistent assets with a wide area collection ability and a variety of viable sensing modalities, satellites seem positioned to shed light on the nature of disaster impacts and support decisions made in the first 24 hours after disasters happen. Satellites are particularly promising for providing information on incidents that occur slowly and in rural areas. However, satellite imagery supports early response decisions and operations for only the most severe incidents in the U.S. This report explores reasons satellite imagery is under-utilized in domestic disaster response and proposes ideas toward solutions. Through systems engineering, combined with quantitative modeling and prototyping, this report offers the following. 1. An analysis of stakeholder decisions and use cases for satellite remote sensing in disasters 2. An evaluation of requirements for imagery and derived data products to support decisions 3. A description and demonstration of a concept of operations and high-level system architecture.
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Summary

Disasters annually cost the U.S. billions of dollars in direct costs and economic loss. In particular, the increasing frequency and intensity of natural hazard incidents, such as hurricanes, tornadoes, floods, and wildfires, strains the nation's emergency management enterprise. Knowing that the current approach to emergency management is unsustainable, practitioners and...

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