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Full list of references

Li, S.; Goldberg, M.D.; Sjoberg, W.; Zhou, L.; Nandi, S.; Chowdhury, N.; Straka, W., III; Yang, T.; Sun, D. Assessment of the Catastrophic Asia Floods and Potentially Affected Population in Summer 2020 Using VIIRS Flood Products. Remote Sens. 2020, 12, 3176. https://doi.org/10.3390/rs12193176

Goldberg, M.D.; Li, S.; Lindsey, D.T.; Sjoberg, W.; Zhou, L.; Sun, D. Mapping, Monitoring, and Prediction of Floods Due to Ice Jam and Snowmelt with Operational Weather Satellites. Remote Sens. 2020, 12, 1865. https://doi.org/10.3390/rs12111865

B. Sjoberg, S. Li and D. Sun, “Global Flood Mapping Services from JPSS,” IGARSS 2018 – 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018, pp. 1605-1607, doi: 10.1109/IGARSS.2018.8517357.

Sanmei Li, DonglianSun, Mitchell Goldberg, Bill Sjoberg, David Santek, Jay P. Hoffman, Mike DeWeese, Pedro Restrepo, Scott Lindsey, Eric Holloway (2017). Automatic near real-time flood detection using Suomi-NPP/VIIRS data, Remote Sensing of Environment, 204 (2018) 672–689

Sanmei Li, Donglian Sun, Mitchell Goldberg & Bill Sjoberg (2015). Object-based automatic terrain shadow removal from SNPP/VIIRS flood maps, International Journal of Remote Sensing, Vol. 36, No. 21, 5504–5522

Sanmei Li, Donglian Sun, Mitchell Goldberg & Antony Stefanidis (2013). Derivation of 30-m-resolution Water Maps from TERRA/MODIS and SRTM. Remote Sensing of Environment 134 (2013) 417–430

Sanmei Li, Donglian Sun, Yunyue Yu, Ivan Csiszar, Antony Stefanidis, & Mitch D. Goldberg (2012). A New Shortwave Infrared (SWIR) Method for Quantitative Water Fraction Derivation and Evaluation with EOS/MODIS and Landsat/TM data. IEEE Transactions on Geoscience and Remote Sensing, Vol. 51, Issue 3

Sanmei Li, Donglian Sun & Yunyue Yu (2013). Automatic cloud-shadow removal fromflood/standing water maps using MSG/SEVIRI imagery, International Journal of Remote Sensing, 34:15, 5487-5502

Donglian Sun, Yunyue Yu, Rui Zhang, Sanmei Li, and Mitchel D. Goldberg (2012). Towards Operational Automatic Flood Detection Using EOS/MODIS data. Photogrammetric Engineering & Remote Sensing, 78 (6)

The Geostationary and JPSS Flood map product is developed by George Mason University and the products are processed in near realtime at the Cooperative Institute for Meteorological Satellite Studies

Funding for this project is provided by NOAA/NESDIS, JPSS Program Office and GOES-R
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