2026-08-11T12:21:48Zhttp://nsidc.org/api/dataset/metadata/oaioai:nsidc.org/MOD10_L2.0052026-06-24T19:16:41Zcumulusecsretirednasa_nsidc_daac
MOD10_L2.005MODIS/Terra Snow Cover 5-Min L2 Swath 500mHall, D. K., Riggs, G. A. & Salomonson, V. V.MODIS/Terra Snow Cover 5-Min L2 Swath 500m2006-12-18Boulder, Colorado USANASA NSIDC DAAC: NASA National Snow and Ice Data Center Distributed Active Archive Center5false10.5067/ACYTYZB9BEOShttps://nsidc.org/sites/default/files/mod10_l2-v005-userguide.pdfMOD10_L2InvestigatorDorothyK.HallNational Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC)Mail stop 614.1GreenbeltMD20771InvestigatorVinceV.Salomonsonvincent.salomonson@utah.edu1-801-585-9492University of UtahDepartment of Meteorology135 S 1460 E, Rm 809Salt Lake CityUT84112USInvestigatorGeorgeA.RiggsGeorge.A.Riggs@nasa.gov1-301-614-5650NASA Goddard Space Flight Center (GSFC)Science Systems and Applications, Inc.Code 614.1GreenbeltMD20771USATechnical ContactNSIDCUser Servicesnsidc@nsidc.org1-303-492-61991-303-492-2468CIRES, 449 UCBUniversity of ColoradoBoulderCO80309-0449USAEARTH SCIENCETERRESTRIAL HYDROSPHERESNOW/ICESNOW COVER EARTH SCIENCECRYOSPHERESNOW/ICESNOW COVER Geoscientific InformationImagery/Base Maps/Earth CoverAntarcticArcticClimatologyDAACECSEOSDISGlobal ChangeLake IceMODIS-projectNASANSIDCNSIDC DAACPolarRemote SensingSnowsnow-coverSnow CoverSnow On IceSwathMODISModerate-Resolution Imaging SpectroradiometerTerraEarth Observing System, Terra (AM-1)2000-02-242017-01-03deprecated-9090-180180ContinentAfricaContinentAntarcticaContinentAsiaContinentEuropeGeographic RegionGlobalGeographic RegionGlobal LandContinentNorth AmericaGeographic RegionPolarContinentSouth AmericaContinentAustralia/new Zealand500 m500 m5 minuteQuality indicators for MODIS snow data can be found in 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 snow cover
* Snow Cover Pixel QA data field.
These quality indicators are generated during production or in post-production scientific and quality checks of the data product.
The AutomaticQualityFlag is automatically set according to conditions for meeting data criteria in the snow mapping 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 snow scientist. Content and explanation of this flag are dynamic so it should always be examined if present in the external metadata file.
The snow 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 snow algorithm makes no snow 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 1 percent local attributes Riggs, Hall, and Salomonson 2006). In addition to these data values, the product contains quality information at the pixel level.
The Snow Cover Pixel QA data field provides additional information on algorithm results for each pixel within a MODIS scene and is used as a measure of usefulness for snow-cover data. The QA data are stored as coded integer values and tell if algorithm results were nominal, abnormal, or if other defined conditions were encountered for a pixel (Riggs, Hall, and Salomonson 2006). For example, intermediate checks for theoretical bounding of reflectance data and the NDSI ratio are made in the algorithm. In theory, reflectance values should lie within the 0-100 percent range, and the NDSI ratio should lie within the -1.0 to +1.0 range. Summary statistics are kept for pixels that exceed these theoretical limits; however, the test for snow is done regardless of violations of these limits.
The NASA Goddard Space Flight Center: MODIS Land Quality Assessment Web site provides updated quality information for each product.EnglishNASA NSIDC DAACNASA National Snow and Ice Data Center Distributed Active Archive Centerhttps://nsidc.org/daacData Center ContactNSIDCUser Servicesnsidc@nsidc.org1-303-492-6199National Snow and Ice Data CenterCIRES, 449 UCBUniversity of ColoradoBoulderCO80309-0449USAFTP0.5 - 10.0 MBGeoTIFFFTP0.5 - 10.0 MBHDF-EOS2Diner, D.J., J.V. Martonchik, C. Borel, S.A.W. Gerstl, H.R. Gordon, Y. Knyazikhin, R. Myneni, B. Pinty, and M.M. Verstraete. 1999. MISR Level-2 surface retrieval algorithm theoretical basis document. Pasadena, CA: Jet Propulsion Laboratory.
Earth Science Data and Information System (ESDIS). 1996. EOS Ground System (EGS) systems and operations concept. Greenbelt, MD: Goddard Space Flight Center.
Hall, D.K., G.A. Riggs, and V.V. Salomonson. September 2001a. Algorithm Theoretical Basis Document (ATBD) for the MODIS Snow-, Lake Ice- and Sea Ice-Mapping Algorithms. Greenbelt, MD: Goddard Space Flight Center.
Hall, D.K., G.A. Riggs, V.V. Salomonson, N.E. DiGirolamo, and K.J. Bayr. 2002. MODIS snow-cover products. Remote Sensing of the Environment 83: 181-194.
Hall, D.K. and J. Martinec. 1985. Remote sensing of ice and snow. London: Chapman and Hall.
Hall, D.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, D.K., J.L. Foster, V.V. Salomonson, A.G. Klein, and J.Y.L. Chien. 2001b. Development of a technique to assess snow-cover mapping accuracy from space. IEEE Transactions on Geoscience and Remote Sensing 39(2): 232-238.
Hall, D.K., G.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.
Klein, A. MODIS Snow Albedo Prototype. 2003.
Klein, A.G., and J. Stroeve. 2002. Development and validation of a snow albedo algorithm for the MODIS instrument. Annals of Glaciology 34: 45-52. Klein, A.G., D.K. Hall, and G.A. Riggs. 1998. Improving snow-cover mapping in forests through the use of a canopy reflectance model. Hydrologic Processes 12(10-11): 1723-1744.
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.
Pearson II, F. 1990. Map projections: theory and applications. Boca Raton, FL: CRC Press, Inc.
Riggs, G.A., D.K. Hall, and V.V. Salomonson. January 2006. MODIS snow products user guide for collection 4 data products.
Salomonson, V. and I. Appel. 2006. Development of the Aqua MODIS NDSI Fractional Snow Cover Algorithm and Validation Results. Transactions on Geoscience and Remote Sensing 44(7):1747-1756.
Salomonson, V. and I. Appel. 2004. Estimating fractional snow cover from MODIS using the normalized difference snow index (NDSI). Remote Sensing of the Environment 89:351-360.
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.The MODIS/Terra Snow Cover 5-Min L2 Swath 500m (MOD10_L2) data set contains snow cover and Quality Assessment (QA) data, latitudes and longitudes in compressed Hierarchical Data Format-Earth Observing System (HDF-EOS) format, and corresponding metadata.VIEW RELATED INFORMATIONhttps://nsidc.org/sites/default/files/mod10_l2-v005-userguide.pdfMODIS/Terra Snow Cover 5-Min L2 Swath 500m, Version 5 User GuidePROJECT HOME PAGEhttp://nsidc.org/data/modis/index.htmlMODIS Data at NSIDCCEOS IDN DIFVERSION 9.92006-12-182026-06-24NSIDCVersion SummaryNSIDCMinor VersionNSIDCLevel of ServiceNo Data AccessNSIDCFull Dataset CitationHall, D. K., Riggs, G. A. & Salomonson, V. V. (2006). <i>MODIS/Terra Snow Cover 5-Min L2 Swath 500m</i>. (MOD10_L2, Version 5). [Data Set]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. <a href="https://doi.org/10.5067/ACYTYZB9BEOS">https://doi.org/10.5067/ACYTYZB9BEOS</a>. [<i><describe subset used if applicable></i>].NSIDCRetiredtrueNSIDCRelated Toolsapplication/vnd.nasa.cmr.umm+jsonfalsefritzdimmt_tool_50907TL3010466318-NSIDC_CPRDNSIDC_CPRD5tool2026-06-24T18:30:53.034Zhttps://zenodo.org/badge/latestdoi/399867529DOWNLOAD SOFTWAREhttps://earthaccess.readthedocs.io/en/stable/DistributionURLNSIDC_CPRD_EARTHACCESSDownloadable Tool0.18.0earthaccessearthaccess is a python library to search and access NASA Earth science data with just a few lines of code.https://github.com/earthaccess-dev/earthaccessVIEW RELATED INFORMATIONGitHub RepositoryPublicationURLDATA ACCESS/RETRIEVALDATA MANAGEMENT/DATA HANDLINGEARTH SCIENCE SERVICESDATA SEARCHDATA MANAGEMENT/DATA HANDLINGEARTH SCIENCE SERVICESPUBLISHERNSIDC DAAC User ServicesEmailnsidc@nsidc.orgPUBLISHERNASA National Snow and Ice Data Center Distributed Active Archive Centerhttps://nsidc.org/daac/NASA NSIDC DAACPUBLISHERNational Snow and Ice Data Centerhttp://nsidc.orgNSIDCDEVELOPERAlaska Satellite Facilityhttps://www.asf.alaska.edu/ASFDEVELOPERInstitute for the Study of Earth, Oceans, and Space, University of New Hampshirehttp://www.eos.unh.edu/UNH/EOSDEVELOPERAtmospheric Science Data Center, Science Directorate, Langley Research Center, NASAhttps://asdc.larc.nasa.gov/NASA/LARC/SD/ASDCMIT License
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See https://github.com/nsidc/earthaccess/releases for more information on the latest version.https://cdn.earthdata.nasa.gov/umm/tool/v1.0UMM-T1.0Python3.8 or higherhttps://earthaccess.readthedocs.io/en/stable/application/vnd.nasa.cmr.umm+jsonfalsecrumlydmmt_tool_12821TL4019517520-NSIDC_CPRDNSIDC_CPRD1tool2026-02-11T17:45:02.724ZGOTO WEB TOOLhttps://search.earthdata.nasa.gov/searchDistributionURLNSIDC_CPRD_NASA_Earthdata_SearchWeb User Interface1NASA Earthdata SearchSearch and order data from all NASA DAACs using spatial and temporal filters in a map interface. Reformatting, reprojecting, and subsetting options are available for some data sets.https://nsidc.org/support/how/search-order-and-customize-nsidc-daac-data-nasa-earthdata-searchVIEW RELATED INFORMATIONHow to search, order, and customize data with NASA Earthdata SearchPublicationURLDATA VISUALIZATIONDATA ANALYSIS AND VISUALIZATIONEARTH SCIENCE SERVICESDATA SEARCHDATA MANAGEMENT/DATA HANDLINGEARTH SCIENCE SERVICESDATA ACCESS/RETRIEVALDATA MANAGEMENT/DATA HANDLINGEARTH SCIENCE SERVICESSERVICE PROVIDERNSIDC DAAC User ServicesEmailnsidc@nsidc.orgSERVICE PROVIDEREarthdata Service DeskEmailsupport@earthdata.nasa.govAUTHORDEVELOPERORIGINATORPUBLISHERMaintenance and Development, Earth Observing System Data and Information System, Earth Observing System,Goddard Space Flight Center, NASAhttp://newsroom.gsfc.nasa.gov/NASA/GSFC/EOS/EOSDIS/EMDChromeFirefoxSafariThis is the most current release of this tool.https://cdn.earthdata.nasa.gov/umm/tool/v1.0UMM-T1.0https://search.earthdata.nasa.gov/search