Publications

Li, S; Sun, DL; Goldberg, MD; Sjoberg, B; Santek, D; Hoffman, JP; DeWeese, M; Restrepo, P; Lindsey, S; Holloway, E (2018). Automatic near real-time flood detection using Suomi-NPP/VIIRS data. REMOTE SENSING OF ENVIRONMENT, 204, 672-689.

Abstract
Near real-time satellite-derived flood maps are invaluable to river forecasters and decision-makers for disaster monitoring and relief efforts. With support from the JPSS (Joint Polar Satellite System) Proving Ground and Risk Reduction (PGRR) Program, flood detection software has been developed using Suomi-NPP/VIIRS (Suomi National Polar-orbiting Partnership/Visible Infrared Imaging Radiometer Suite) imagery to automatically generate near real-time flood maps for National Weather Service (NWS) River Forecast Centers (RFC) in the USA. The software, which is called VIIRS NOAA GMU Flood Version 1.0 (hereafter referred to as VNG Flood V1.0), consists of a series of algorithms that include water detection, cloud shadow removal, terrain shadow removal, minor flood detection, water fraction retrieval, and floodwater determination. The software is designed for flood detection in any land region between 80 degrees S and 80 degrees N, and it has been running routinely with direct broadcast SNPP/VIIRS data at the Space Science and Engineering Center at the University of Wisconsin-Madison (UW/SSEC) and the Geographic Information Network of Alaska at the University of Alaska-Fairbanks (UAF/GINA) since 2014. Near real-time flood maps are distributed via the Unidata Local Data Manager (LDM), reviewed by river forecasters in AWIPS-II (the second generation of the Advanced Weather Interactive Processing System) and applied in flood operations. Initial feedback from operational forecasters on the product accuracy and performance has been largely positive. The software capability has also been extended to areas outside of the USA via a case-driven mode to detect major floods all over the world. Offline evaluation efforts include the visual inspection of over 10,000 VIIRS false-color composite images, an inter-comparison with MODIS automatic flood products and a quantitative validation using Landsat imagery. The steady performance from the 3-year routine process and the promising evaluation results indicate that VNG Flood V1.0 has a high feasibility for flood detection at the product level.

DOI:
10.1016/j.rse.2017.09.032

ISSN:
0034-4257