MODIS/Aqua Snow Cover 5-Min L2 Swath 500m, Version 4  View Catalog Page Entry ID
MYD10_L2
Summary
MODIS/Aqua Snow Cover 5-Min L2 Swath 500m (MYD10_L2) contains snow cover and quality assurance (QA) data, latitudes, and longitudes in HDF-EOS format, along with corresponding metadata. Latitude and longitude geolocation fields are at 5 km resolution, while all other fields are at 500 m resolution. Version 4 (V004), the latest version of MODIS data available, has two separate snow cover fields: one incorporating the original cloud mask, and another using a less cloud-conservative mask. MODIS/Aqua V004 data extend from 04 July 2002 to present. MODIS snow cover data are based on a snow mapping algorithm that employs a Normalized Difference Snow Index (NDSI) and other criteria tests. The only data available for Version 4 (V004) is the Golden Month, which is a sample of V004 data covering the time period 29 August 2002 (day of year 241) through 7 October 2002 (day of year 280). The Golden Month is only available by special request by contacting NSIDC User Services.
Please note that NSIDC now has a complete series of Version 5 data, which is the highest version number now available and represents the best quality of data.
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Caption: MYD10_L2 Version 4 data, 15 January 2004
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Geographic Coverage
Spatial Coordinates:
N: 90°
S: -90°
E: 180°
W: -180°
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Data Set Citation
Dataset Creator: D. Hall, V. Salomonson
Dataset Title: MODIS/Aqua Snow Cover 5-Min L2 Swath 500m, Version 4
Dataset Release Date: 2000-09-01
Dataset Release Place: Boulder, CO
Dataset Publisher: National Snow and Ice Data Center (NSIDC)
Version: 4
Data Presentation Form: Digital media
Online Resource: http://nsidc.org/data/myd10_l2.html
Temporal Coverage
Start Date: 2002-07-04
Stop Date: 2006-12-31
Data Resolution
Latitude Resolution: 500 m
Longitude Resolution: 500 m
Temporal Resolution: 5 min
Location Keywords
- Geographic Region Global Land
Science Keywords
- Cryosphere Snow/Ice Lake Ice
- Cryosphere Snow/Ice Snow Cover
- Cryosphere Snow/Ice Snow Cover Fractional Snow Cover
- Terrestrial Hydrosphere Snow/Ice Lake Ice
- Terrestrial Hydrosphere Snow/Ice Snow Cover
- Terrestrial Hydrosphere Snow/Ice Snow Cover Fractional Snow Cover
Ancillary Keywords
- Antarctic
- Arctic
- Climatology
- DAAC
- ECS
- EOS PM-1
- EOSDIS
- Global Change
- Lake Ice
- NASA
- NSIDC
- Polar
- Remote Sensing
- Snow
- Snow Cover
- Snow On Ice
- Swath
- Climatology/Meteorology/Atmosphere
Platform
- AQUA Earth Observing System, AQUA
Instrument
- MODIS Moderate-Resolution Imaging Spectroradiometer
- SPECTRORADIOMETERS
Project
- EOSDIS Earth Observing System Data Information System
- ESIP Earth Science Information Partners Program
Quality
Quality indicators for MODIS snow data are represented by the AutomaticQualityFlag and the ScienceQualityFlag metadata objects and their corresponding explanations, AutomaticQualityFlagExplanation and ScienceQualityFlagExplanation, in the CoreMetadata.0 global attribute and also in the Snow Cover PixelQA data field. These are generated during production or in post-product 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 are set 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.
The Snow Cover PixelQA field provides additional information on algorithm results for each pixel within a spatial context, and is used as a measure of usefulness for snow-cover data. QA data are stored as bit flags, and QA information is extracted by reading the bits within a byte. (See MODIS Snow Cover Quality Assurance Fields.) The QA information tells if algorithm results were nominal, abnormal, or if other defined conditions were encountered for a pixel (Riggs, Hall, and Salomonson 2003). 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. Violations are tracked and written as Auto_check_QA local attributes as they suggest that error or other anomalies may have been introduced into the input data, indicating the need for further investigation. The snow algorithm also 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. A snow spatial QA bit is set to indicate the cause, and the algorithm moves to the next pixel. Summary statistics are calculated for these conditions and reported as Valid EV Obs Band x local attributes (Riggs, Hall, and Salomonson 2003).
The MODIS Land Quality Assurance Web site provides updated quality information for each product.
Data Set Progress
COMPLETE
Originating Center
MODAPS
Data Center
National Snow and Ice Data Center
Data Center URL: http://nsidc.org
Data Set ID: MYD10_L24
Data Center Personnel
Name: NSIDC User Services
Phone: +1 (303) 492-6199
Fax: +1 (303) 492-2468
Email: nsidc@nsidc.org
Contact Address:
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
City: Boulder
Province or State: CO
Postal Code: 80309-0449
Country: USA
NSIDC Distributed Active Archive Center
Data Center URL: http://nsidc.org/daac/index.html
Data Set ID: MYD10_L24
Data Center Personnel
Name: NSIDC DAAC User Services
Phone: +1 (303) 492-6199
Fax: +1 (303) 492-2468
Email: nsidc@nsidc.org
Contact Address:
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
City: Boulder
Province or State: CO
Postal Code: 80309-0449
Country: USA
Distribution
Distribution Media: upon request
Distribution Size: 0.5 - 10.0 MB
Distribution Format: GeoTIFF
Distribution Media: upon request
Distribution Size: 0.5 - 10.0 MB
Distribution Format: HDF-EOS
Personnel
Dorothy K. Hall
Role: INVESTIGATOR
Contact Address:
National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC)
Mail stop 614.1
City: Greenbelt
Province or State: MD
Postal Code: 20771
Vince V. Salomonson
Role: INVESTIGATOR
Contact Address:
Room 809 WBB
Department of Meteorology
University of Utah
City: Salt Lake City
Province or State: UT
Postal Code: 84112
Country: US
NSIDC USER SERVICES
Role: TECHNICAL CONTACT
Phone: +1 (303) 492-6199
Fax: +1 (303) 492-2468
Email: nsidc@nsidc.org
Contact Address:
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
City: Boulder
Province or State: CO
Postal Code: 80309-0449
Country: USA
George A. Riggs
Role: TECHNICAL CONTACT
Contact Address:
NASA Goddard Space Flight Center (GSFC)
Science Systems and Applications, Inc.
Mail stop 614.1
City: Greenbelt
Province or State: MD
Postal Code: 20771
Related URL
VIEW PROJECT HOME PAGE
MODIS DAAC page at NSIDC
Reference
Diner, 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., 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. and J. Martinec. 1985. Remote sensing of ice and snow. London: Chapman and Hall.
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., 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.
Hapke, B. 1993. Theory of reflectance and emittance spectroscopy. Cambridge: Cambridge University Press.
Klein, A. MODIS Snow Albedo Prototype. 2003. Accessed July 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.
MODIS Science and Instrument Team. MODIS Web. July 2003. Accessed October 2000.
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 2003. MODIS snow products user guide for collection 4 data products. .
Riggs, G. A., D. K. Hall, and V. V. Salomonson, December 2006. MODIS snow products user guide to collection 5. .
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.
Metadata Name and Version
Metadata Name: CEOS IDN DIF
Metadata Version: 9.7
Creation and Review Dates
DIF Creation Date: 2007-01-19
Last DIF Revision Date: 2004-11-16
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