IN34B-07
APPLICATION OF SNPP/VIIRS DATA IN NEAR REAL-TIME SUPRA-SNOW/ICE FLOOD DETECTION
Wednesday, 16 December 2015: 17:30
2018 (Moscone West)
Sanmei Li1, Donglian Sun1, Mitch Goldberg2, Bill Sjoberg3, Edward William Plumb4, Eric Holloway5, Scott Lindsey5 and Melissa Kreller4, (1)George Mason University Fairfax, Fairfax, VA, United States, (2)NOAA Camp Springs, Camp Springs, MD, United States, (3)NOAA, Boulder, CO, United States, (4)National Weather Service Fairbanks, Fairbanks, AK, United States, (5)NOAA National Weather Service Alaska-Pacific River Forecast Center, Anchorage, AK, United States
Abstract:
Supra-snow/ice flood is very common in high latitude areas from winter to spring break-up seasons along rivers flowing to even higher latitude areas, but this flood type doesn’t draw much attention due to poor ground conditions for river watch and ground observations. Satellite data from SNPP/VIIRS (Suomi-National Polar-orbit Partnership/Visible/Infrared Imager Radiometer Suite) instead have shown great advantages in supra-snow/ice flood detection due to its large swath coverage, multiple daily observations in high latitude areas and moderate spatial resolution. Thus, methods for supra-snow/ice water detection were developed to detect near real-time supra-snow/ice floods automatically using SNPP/VIIRS imagery. The methods were mainly based on spectral features of supra-snow/ice floodwater, assisting by geometry-based algorithm and object-based algorithm to remove cloud shadows and terrain shadows over snow/ice surface. The detected supra-snow/ice floodwater was further applied in water fraction retrieval for better representation of flood extent using a modified histogram method based on linear combination model. The developed methods were successfully applied in dynamic monitoring of 2015’s supra-snow/ice flood along Sag River in Alaska, which was claimed as a state disaster by Alaska state government, and further tested with more than 1000 VIIRS granules year around. Analyses through visual inspection with VIIRS false-color composite images and quantitative comparison with Landsat-8 OLI images show promising and robust performance in detection of supra-snow/ice floodwater, indicating a high feasibility for the method to be applied in operations for near real-time supra-snow/ice flood detection.