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Near Real-Time Flood Monitoring and Impact Assessment SystemsFloods are the costliest natural disaster, causing approximately 6.8 million deaths in the twentieth century alone. Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD. Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries. Projections by the Intergovernmental Panel on Climate Change (IPCC) suggest that precipitation extremes, rainfall intensity, storm intensity, and variability are increasing due to climate change. Increasing hydrologic uncertainty will likely lead to unprecedented extreme flood events. As such, there is a vital need to enhance and further develop traditional techniques used to rapidly assess flooding and extend analytical methods to estimate impacted population and infrastructure. Measuring flood extent in situ is generally impractical, time consuming, and can be inaccurate. Remotely sensed imagery acquired from space-borne and airborne sensors provides a viable platform for consistent and rapid wall-to-wall monitoring of large flood events through time. Terabytes of freely available satellite imagery are made available online each day by NASA, ESA, and other international space research institutions. Advances in cloud computing and data storage technologies allow researchers to leverage these satellite data and apply analytical methods at scale. Repeat-survey earth observations help provide insight about how natural phenomena change through time, including the progression and recession of floodwaters. In recent years, cloud-penetrating radar remote sensing techniques (e.g., Synthetic Aperture Radar) and high temporal resolution imagery platforms (e.g., MODIS and its 1-day return period), along with high performance computing infrastructure, have enabled significant advances in software systems that provide flood warning, assessments, and hazard reduction potential. By incorporating social and economic data, researchers can develop systems that automatically quantify the socioeconomic impacts resulting from flood disaster events.
Document ID
Document Type
Book Chapter
Ahamed, Aakash (Universities Space Research Association Greenbelt, MD, United States)
Bolten, John (NASA Goddard Space Flight Center Greenbelt, MD United States)
Doyle, Colin (Texas Univ. Austin, TX, United States)
Fayne, Jessica (South Carolina Univ. Columbia, SC, United States)
Date Acquired
June 29, 2017
Publication Date
October 4, 2016
Publication Information
Publication: Remote Sensing of Hydrological Extremes
ISSN: 2198-0721
ISBN: 2198-0721
Subject Category
Meteorology and Climatology
Earth Resources and Remote Sensing
Report/Patent Number
Distribution Limits