MODIS/Terra Coarse Sea Ice Extent 5-Min L2 Swath 5km (MOD29) data set contains fields for sea ice by reflectance, sea ice by reflectance pixel Quality Assessment (QA), Ice Surface Temperature (IST), IST pixel QA, latitudes, and longitudes in Hierarchical Data Format-Earth Observing System (HDF-EOS) format, along with corresponding metadata. Latitude and longitude geolocation fields are at 5 km ... resolution, while all other fields are at 1 km resolution. The sea ice algorithm uses a Normalized Difference Snow Index (NDSI) modified for sea ice to distinguish sea ice from open ocean based on reflective and thermal characteristics. Data are stored in HDF-EOS format, and are available from 24 February 2000 to present via FTP. Data can also be obtained in GeoTIFF format by ordering the data through the Data Pool.
All MODIS/Terra sea ice products are considered validated or at stage 2 meaning that accuracy has been assessed over a widely distributed set of locations and time periods via several ground-truth and validation campaigns. Quality indicators for MODIS sea ice data can be found in the following three places: * AutomaticQualityFlag and the ScienceQualityFlag metadata objects and their ... corresponding explanations: AutomaticQualityFlagExplanation and ScienceQualityFlagExplanation located in the CoreMetadata.0 global attributes * Custom local attributes associated with each Scientific Data Set (SDS), for example Ice Surface Temperature * The Pixel QA SDS that accompanies each data field, for example, Ice Surface Temperature Pixel QA. These quality indicators are generated during production or in post-production scientific and quality checks of the data product. For more information on local and global attributes, go to one of the following links: * MOD29 and MYD29 Local Sea Ice Attributes, Version 5 * MOD29 and MYD29 Global Sea Ice Attributes, Version 5 An AutomaticQualityFlag for each SDS is automatically set according to conditions for meeting data criteria in the algorithm. In most cases, the flag is set to either Passed or Suspect, and in rare instances, it may be set to Failed. Suspect means that a significant percentage of the data were anomalous and that further analysis should be done to determine the source of anomalies. The AutomaticQualityFlagExplanation contains a brief message explaining the reason for the setting of the AutomaticQualityFlag. The ScienceQualityFlag and the ScienceQualityFlagExplanation maybe updated after production, either after an automated QA program is run or after the data product is inspected by a qualified scientist. Content and explanation of this flag are dynamic so it should always be examined if present in the external metadata file. In the MYD29 data product, there are two instances of the ScienceQualityFlagExplanation, one for sea ice determined by reflectance data and one for IST written in the metadata The sea ice algorithm identifies missing data and reports them in the output product. Certain expected anomalous conditions may exist with the input data such as a few missing lines or unusable data from the MODIS sensor. In these cases, the algorithm makes no decision for an affected pixel. Summary statistics are calculated for these conditions and reported as Valid EV Obs Band X percent and Saturated EV Obs Band X percent local attributes. Where X equals 2, 4, or 6 for Sea Ice by Reflectance and 31 or 32 for IST (Riggs, Hall, and Salomonson 2003). The IST Pixel QA and the Sea Ice by Reflectance Pixel QA data fields provide additional information on algorithm results for each pixel within a MODIS scene, and are used as a measure of usefulness for sea ice data. The QA data are stored as coded integer values and tells if algorithm results were nominal, abnormal, or if other defined conditions were encountered for a pixel. For example, intermediate checks for theoretical bounding of reflectance data and the NDSI ratio are made in the algorithm. Reflectance values should lie within the 0-100 percent range, and the NDSI ratio should lie within the -1.0 to +1.0 range. If these limits are violated, the test for sea ice is still done, but the quality flag is set to Other quality in the Pixel QA field (Riggs, Hall, and Salomonson 2003). The NASA Goddard Space Flight Center: MODIS Land Quality Assessment Web site provides updated quality information for each product.
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Earth Science Data and Information System (ESDIS). 1996. EOS Ground System (EGS) systems and operations concept. Greenbelt, MD: Goddard Space Flight Center. Hall, Dorothy K., J. L. Foster, D. L. Verbyla, A. G. Klein, and C. S. Benson. 1998. Assessment of snow cover mapping accuracy in a variety of vegetation cover densities in central Alaska. Remote Sensing of the Environment 66:129-137. Hall, ... Dorothy K., Jeffrey R. Key, Kimberly A. Casey, George A. Riggs, and Donald Cavalieri. May 2004. Sea ice surface temperature product from MODIS. IEEE Transactions on Geoscience and Remote Sensing 42:5. Hall, Dorothy K. and J. Martinec. 1985. Remote sensing of ice and snow. London: Chapman and Hall. Hall, Dorothy K., George A. Riggs, and Vincent V. Salomonson. 1995. Development of methods for mapping global snow cover using Moderate Resolution Imaging Spectroradiometer (MODIS). Remote Sensing of the Environment 54(2): 127-140. Hall, Dorothy K., George A. Riggs, and Vincent V. Salomonson. September 2001. Algorithm Theoretical Basis Document (ATBD) for the MODIS Snow-, Lake Ice- and Sea Ice-Mapping Algorithms. Greenbelt, MD: Goddard Space Flight Center. <http://modis-snow-ice.gsfc.nasa.gov/atbd.html> . Hall, Dorothy K., George A. Riggs. 2006. Assessment of errors in the MODIS suite of snow-cover products. Hydrological Processes, in press. Hapke, B. 1993. Theory of reflectance and emittance spectroscopy. Cambridge: Cambridge University Press. Key, J. R., J. B. Collins, Chuck Fowler, and R. S. Stone. 1997.High latitude surface temperature estimates From thermal satellite data. Remote Sensing of the Environment 61:302-309. Key, J. R., J. A. Maslanik, T. Papakyriakou, Mark C. Serreze, and A. J. Schweiger. 1994. On the validation of satellite-derived sea ice surface temperature. Arctic 47:280-287. Markham, B. L. and J. L. Barker. 1986. Landsat MSS and TM post-calibration dynamic ranges, exoatmospheric reflectances and at-satellite temperatures. EOSAT Technical Notes 1:3-8. MODIS Characterization and Support Team (MCST). 2000. MODIS Level-1B product user's guide for Level-1B Version 2.3.x Release 2. MCST Document #MCM-PUG-01-U-DNCN. MODIS Science and Instrument Team. MODIS Web. July 2003. <http://modis.gsfc.nasa.gov/> Accessed October 2000. Pearson II, F. 1990. Map projections: theory and applications. Boca Raton, FL: CRC Press, Inc. Riggs, George A., Dorothy K. Hall, and Vincent V. Salomonson. February 2003. MODIS sea ice products user guide. <http://modis-snow-ice.gsfc.nasa.gov/siugkc.html> . Riggs, George A., Dorothy K. Hall, and S. A. Ackerman. 1999. Sea ice extent and classification mapping with the Moderate Resolution Imaging Spectroradiometer Airborne Simulator. Remote Sensing of the Environment 68: 152-163. Scambos, Ted A., Terry M. Haran, and Robert Massom. In press. Validation of AVHRR and MODIS Ice Surface Temperature Products Using In Situ Radiometers. Annals of Glaciology 44. Wiscombe, W. J. and S. G. Warren. 1980. A Model for the Spectral Albedo of Snow I: Pure Snow. Journal of the Atmospheric Sciences 37:2712-2733.