Blu‑H VIIRS archive on Azure

Licensing

Attribution & licensing

Source data — public domain

The VIIRS flood products are works of US federal agencies, not subject to US copyright (17 U.S.C. § 105). Both agencies confirm open access:

Derivatives — CC0 1.0 Universal

All derivatives Blu‑H produces (COGs, STAC items and collections, indices and metadata) are dedicated to the public domain under Creative Commons CC0 1.0.

The person who associated a work with this deed has dedicated the work to the public domain by waiving all of their rights to the work worldwide under copyright law, including all related and neighbouring rights, to the extent allowed by law. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.

Attribution (requested, not required)

Not legally required, but appreciated so users can trace provenance. Suggested:

Source data: VIIRS flood products produced by the Cooperative Institute for Meteorological Satellite Studies (CIMSS) at UW-Madison SSEC, funded by NOAA / NESDIS and the JPSS Program Office. Cloud-native derivatives (COGs, STAC catalog) hosted by Blu‑H and dedicated to the public domain under CC0 1.0.

Machine-readable (STAC providers)

"providers": [
  {
    "name": "NOAA/NESDIS/JPSS",
    "roles": ["producer"],
    "url": "https://www.nesdis.noaa.gov/"
  },
  {
    "name": "CIMSS / UW-Madison SSEC",
    "roles": ["processor"],
    "url": "https://www.ssec.wisc.edu/"
  },
  {
    "name": "Blu-H",
    "roles": ["host"],
    "url": "https://github.com/Blu-H/VIIRS"
  }
]

Scientific references

The VIIRS flood-detection algorithm and its derived products are described in the peer-reviewed literature below. Algorithm development was led at George Mason University with processing at the Cooperative Institute for Meteorological Satellite Studies (CIMSS), funded by NOAA / NESDIS, the JPSS Program Office and GOES‑R. This list mirrors the SSEC full list of references.

  1. Li, S.; Goldberg, M.D.; Sjoberg, W.; Zhou, L.; Nandi, S.; Chowdhury, N.; Straka, W., III; Yang, T.; Sun, D. (2020). Assessment of the Catastrophic Asia Floods and Potentially Affected Population in Summer 2020 Using VIIRS Flood Products. Remote Sens. 12, 3176. doi:10.3390/rs12193176
  2. Goldberg, M.D.; Li, S.; Lindsey, D.T.; Sjoberg, W.; Zhou, L.; Sun, D. (2020). Mapping, Monitoring, and Prediction of Floods Due to Ice Jam and Snowmelt with Operational Weather Satellites. Remote Sens. 12, 1865. doi:10.3390/rs12111865
  3. Sjoberg, B.; Li, S.; Sun, D. (2018). Global Flood Mapping Services from JPSS. IGARSS 2018 — IEEE International Geoscience and Remote Sensing Symposium, 1605–1607. doi:10.1109/IGARSS.2018.8517357
  4. Li, S.; Sun, D.; Goldberg, M.; Sjoberg, B.; Santek, D.; Hoffman, J.P.; 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.
  5. Li, S.; Sun, D.; Goldberg, M.; Sjoberg, B. (2015). Object-based automatic terrain shadow removal from SNPP / VIIRS flood maps. International Journal of Remote Sensing 36(21), 5504–5522.
  6. Li, S.; Sun, D.; Goldberg, M.; Stefanidis, A. (2013). Derivation of 30-m-resolution Water Maps from TERRA / MODIS and SRTM. Remote Sensing of Environment 134, 417–430.
  7. Li, S.; Sun, D.; Yu, Y.; Csiszar, I.; Stefanidis, A.; Goldberg, M.D. (2012/2013). 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 51(3).
  8. Li, S.; Sun, D.; Yu, Y. (2013). Automatic cloud-shadow removal from flood / standing water maps using MSG / SEVIRI imagery. International Journal of Remote Sensing 34(15), 5487–5502.
  9. Sun, D.; Yu, Y.; Zhang, R.; Li, S.; Goldberg, M.D. (2012). Towards Operational Automatic Flood Detection Using EOS / MODIS data. Photogrammetric Engineering & Remote Sensing 78(6).
  10. Li, S.; Sun, D. (2013). Development of an integrated high resolution flood product with multi-source data. UMI Dissertations Publishing. ISBN 9781303635939.
  11. Li, S.; Sun, D.; Goldberg, M.D.; Kalluri, S.; Sjoberg, B.; Lindsey, D.; Hoffman, J.P.; et al. (2022). A downscaling model for derivation of 3-D flood products from VIIRS imagery and SRTM / DEM. ISPRS Journal of Photogrammetry and Remote Sensing 192, 279–298.
  12. Li, S.; Goldberg, M.; Kalluri, S.; Lindsey, D.T.; Sjoberg, B.; Zhou, L.; Helfrich, S.; et al. (2022). High resolution 3D mapping of hurricane flooding from moderate-resolution operational satellites. Remote Sensing 14(21), 5445.
  13. Li, S.; Sun, D.; Goldberg, M.D.; Lindsey, D. (2021). Automatic Near-Real-Time Flood Mapping from Geostationary Low Earth Orbiting Satellite Observations. In Global Drought and Flood: Observation, Modeling, and Prediction, 61–97.

Source code licence

Source code in the Blu-H/VIIRS repository is licensed under Apache License 2.0, separate from the data licence above.