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A presentation by Craig J. Evanego - U.S. National Ice Center

Remote Sensing and Monitoring Ice Conditions in the Great Lakes. A presentation by Craig J. Evanego - U.S. National Ice Center. Overview: The Use of Remotely Sensed Data for Great Lakes Ice Analysis. I. Purpose : Importance of monitoring ice conditions in the Great Lakes

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A presentation by Craig J. Evanego - U.S. National Ice Center

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  1. Remote Sensing and Monitoring Ice Conditions in the Great Lakes A presentation by Craig J. Evanego - U.S. National Ice Center

  2. Overview: The Use of Remotely Sensed Data for Great Lakes Ice Analysis • I. Purpose: Importance of monitoring ice conditions in the Great Lakes • II. Present: Existing data sources • III. Future: Capabilities/advantages of a new data source

  3. North American Ice Service (NAIS)

  4. NAIS Mission • Combine strengths of each Ice Center • Offer an integrated ice information service for North America • High quality and consistency • Single point-of-access for users • Optimize resources of both countries & reduce duplication of effort • Data access, system development, research, etc • Built around a common “public” suite of products • Each center maintains ability to provide service for individual clients independently

  5. NAIS Ice Analysis of the Great Lakes

  6. Typical Ice Conditions in the Great Lakes

  7. Importance of Monitoring Ice Conditions in the Great Lakes • Aid the Safety of Winter Navigation and Coast Guard Operations 2) Monitoring Climate Variability and Change

  8. Monitoring Great Lakes Ice Conditions to Aid Safety of Navigation

  9. Monitoring Great Lakes Ice Conditions to Aid Safety of Navigation • Special chart, derived from NAIS ice analysis, designed specifically for Coast Guard operations • Shows thickest forms of ice present across the Great Lakes

  10. Monitoring Great Lakes Ice Cover to Monitor Climate Variability & Change from Assel (2003): from Assel et al (2003): • Great Lakes ice cover is a sensitive indicator of regional climate and climate change (Assel and Rodionov, 1998)

  11. NAIS Ice Analysis of the Great Lakes: Primary Remote Sensing Data Sources • Synthetic Aperture Radar (SAR) • - RADARSAT • - ENVISAT 2. Moderate Resolution Imaging Spectroradiometer (MODIS) 3. DMSP Operational Linescan System (OLS) 4. Advanced Very High Resolution Radiometer (AVHRR) 5. Geostationary Operational Environmental Satellites (GOES)

  12. Great Lakes SAR imagery • Primary data source for the NAIS Great Lakes ice analysis • Currently using data from Radarsat-1 and Envisat • Advantages: • SAR imagery is all-weather • Excellent spatial resolution (ScanSAR Wide Mode = 100 m) • Using ScanSAR Wide mode, can get complete coverage of Lakes 2-3 times per week.

  13. Great Lakes SAR imagery - Annotated

  14. Ct  -  Total concentration of ice in area, reported in tenths. Ca Cb Cc  -  Partial concentration (Ca, Cb, Cc) are also reported in tenths. Reported in order of decreasing thickness, Ca is the concentration of the thickest ice and Cc is the concentration of the thinnest ice. Sa Sb Sc  -  Stage of ice development (Sa, Sb, Sc) is listed in decreasing order of thickness.  These codes are directly correlated with the partial concentrations above.  That is, Ca is the concentration of stage Sa, and so on. Fa Fb Fc  -  Predominant form of ice (i.e. floe size, fast ice) corresponding to Sa, Sb and Sc, respectively. Explanation of the WMO “Egg Code”

  15. Explanation of Coding for Lake Ice Ice TypeCodeThickness New Ice 1 0-10 cm Thin Lake Ice 4 10-15 cm Medium Lake Ice 5 15-30 cm Thick Lake Ice 7 30-70 cm Very Thick Lake Ice 1 >70 cm

  16. Great Lakes SAR imagery - Annotated

  17. Great Lakes SAR imagery - Annotated

  18. Great Lakes MODIS imagery • Along with SAR, an important data source for the NAIS Great Lakes ice analysis. • Advantages: • Good spatial resolution (up to 250 m) • Available in ‘true color’ • Data available over entire Lakes region each day • Available, in GeoTiff format, from sites on WWW

  19. Great Lakes MODIS imagery March 12, 2006

  20. Great Lakes MODIS imagery – NOAA Coastwatch

  21. Great Lakes MODIS imagery • ‘True color’ • Visible imagery • High spatial resolution at 250 m. • GeoTiff format ideal for use in NIC analysis.

  22. Great Lakes MODIS imagery Visible MODIS image from December 2, 2005 (Note new ice forming along western shore of southern Green Bay.)

  23. Great Lakes MODIS imagery - Annotated

  24. Great Lakes DMSP OLS imagery • Another commonly used data source, used in conjunction with SAR and MODIS data, for the NAIS Great Lakes ice analysis. • Advantages: • Good spatial resolution (up to 550 m) • Data available over entire Lakes region each day

  25. Great Lakes DMSP OLS imagery - Annotated

  26. NAIS Analysis Software • Based on ESRI’s ArcGIS software • Allows for editing of lines and egg code attributes, as well as chart generation

  27. Ice Analysis in the Future • RADARSAT-2 • Expected launch in December of 2006. • RADARSAT-2 will have the capability to send and receive both H and V in four states: HH, HV, VH, and VV • 1st commercial spaceborne SAR to offer quadrature-polarimetry ("quad-pol") capability • Polarimetric data – could be used to locate regions of severe ice deformation, which is a primary concern for winter navigation in the Great Lakes

  28. Multiple Polarization: RADARSAT-2 vs. its Predecessors • Polarimetric data available on RADARSAT-2 will enable analysts to better interpret regions of ice deformation.

  29. Use of Polarimetric Data to Identify Region of Severe Ice Deformation

  30. Multiple Polarization: Cross-Polarization HH- polarized HV- polarized (from Van der Sanden and Ross, 2001)

  31. Questions / Comments?

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