MODIS/Aqua Snow Cover 8-Day L3 Global 500m Grid, Version 5

Summary

The MODIS/Aqua Snow Cover 8-Day L3 Global 500m Grid (MYD10A2) data set contains data fields for maximum snow cover extent over an eight-day compositing period and a chronology of snow occurrence observations in compressed Hierarchical Data Format-Earth Observing System (HDF-EOS) format, along with corresponding metadata. MOD10A2 consists of 1200 km by 1200 km tiles of 500 m resolution data gridded in a sinusoidal map projection. The Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data are based on a snow mapping algorithm that employs a Normalized Difference Snow Index (NDSI) and other criteria tests.

Citing These Data

We kindly request that you cite the use of this data set in a publication using the following citation. For more information, see our Use and Copyright Web page.

The following example shows how to cite the use of this data set in a publication. List the principal investigators, year of data set release, data set title and version number, dates of the data you used (for example, December 2003 to March 2004), publisher: NSIDC, and digital media.

Hall, Dorothy K., George A. Riggs, and Vincent V. Salomonson. 2007, updated weekly. MODIS/Aqua Snow Cover 8-Day L3 Global 500m Grid V005, [list the dates of the data used]. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media.

Overview Table


Category Description
Data format HDF-EOS version 2.9. GeoTIFF available through Reverb | ECHO, NASA's Next Generation Earth Science Discovery tool.
Spatial coverage and resolution Coverage is global, but only land tiles are produced. Gridded resolution is 500 m.
Temporal coverage and resolution MODIS data extends from 04 July 2002 to present.
Tools for accessing and analyzing data Land Processes Distributed Active Archive Center (LP DAAC): MODIS Reprojection Tool Distribution Page
MODIS: MODIS Land Discipline Group (MODLAND) Tile Calculator
Hierarchical Data Format - Earth Observing System (HDF-EOS)
MODIS Rapid Response System
NASA Goddard Space Flight Center: MODIS Land Global Browse Images
HEG HDF-EOS to GeoTIFF Conversion Tool
National Center for Supercomputing Applications (NCSA) HDFView
The MODIS Conversion Toolkit (MCTK)
Data range
Maximum Snow Extent Coded Integer Values
Sample Value
Explanation
0
data missing
1
no decision
11
night
25
no snow
37
lake
3
ocean
50
cloud
100
lake ice
200
snow
254
detector saturated
255
fill

For more information regarding the coded integer value descriptions, please see the MOD10A2 and MYD10A2 Local Snow Cover Attributes, Version 5 document.

See Summary of MOD10A2/MYD10A2 Bit Values for an interpretation of bit values and resulting integer values for the Eight Day Snow Cover field.
Grid type and size Data are gridded in equal-area tiles in a sinusoidal projection. Each tile consists of a 1200 km by 1200 km data array which corresponds to 2400 pixels by 2400 pixels at 500 m resolution.
File naming convention Example: MOD10A2.A2003138.h03v06.005.2003143062148.hdf
File size 0.05 - 3 MB using HDF compression
Parameter(s) Maximum Snow Extent
Eight Day Snow Cover
Procedures for obtaining data Please see Ordering MODIS Products from NSIDC for a list of order options.

Table of Contents

1. Contacts and Acknowledgments
2. Data Access and Tools
3. Detailed Data Description
4. Data Processing
5. Data Acquisition
6. References and Related Publications
7. Document Information

1. Contacts and Acknowledgments

Investigator(s) Name and Title

Principal Investigators

Dorothy K. Hall
National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC)
Mailstop 614.1
Greenbelt, MD 20771

Vincent V. Salomonson
Room 809 WBB
Department of Meteorology
University of Utah
Salt Lake City, UT 84112

Support Investigator

George A. Riggs
NASA GSFC
Science Systems and Applications, Inc.
Mailstop 614.1
Greenbelt, MD 20771

Technical Contact

NSIDC User Services
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO 80309-0449  USA
phone: +1 303.492.6199
fax: +1 303.492.2468
form: Contact NSIDC User Services
e-mail: nsidc@nsidc.org

2. Data Access and Tools

Data Access Aids

The following sites can help you select appropriate MODIS data for your study:

Data Access Tools

Please see the Ordering MODIS Products from NSIDC Web site for a list of order options.

Data Analysis Tools

Related Data Collections

See the MODIS Data at NSIDC: Data Summaries Web page for other MODIS snow and sea ice products available from NSIDC.

3. Detailed Data Description

Algorithms that generate snow cover products are continually being improved as limitations become apparent in early versions of data. As a new algorithm becomes available, a new version of data is released. Users are encouraged to work with the most current version of MODIS data available, which is the highest version number. Version 5 (V005), also known as Collection 5, is the most current version of data available from NSIDC.

Please visit the following sites for more information about the V005 data, known data problems, the production schedules, and future plans:

Format

MODIS snow products are archived in compressed HDF-EOS format, which employs point, swath, and grid structures to geolocate the data fields to geographic coordinates. This data compression should be transparent to most users since HDF capable software tools automatically uncompress the data. Various software packages, including several in the public domain, support the HDF-EOS data format. See the Software section for details. Also, see the Hierarchical Data Format - Earth Observing System (HDF-EOS) Web site for more information about the HDF-EOS data format, as well as tutorials in uncompressing the data and converting data to binary format.

Data can also be obtained in GeoTIFF format by ordering the data through the Data Pool.

MOD10A2 consists of 2400 x 2400 cells of tiled data in a sinusoidal projection. Each data granule contains the following HDF-EOS local attribute fields, which are stored with their associated Scientific Data Set (SDS):

Each data granule also contains metadata either stored as global attributes or as HDF-predefined fields, which are stored with each SDS.

A Summary of MOD10A2/MYD10A2 Bit Values provides an interpretation of bit values and resulting integer values for the Eight Day Snow Cover Field.

External Metadata File

A separate ASCII text file containing metadata with a .xml file extension accompanies the HDF-EOS file. The metadata file contains some of the same metadata as in the product file, but also includes other information regarding archiving, user support, and post-production Quality Assessment (QA) relative to the granule ordered. The post-production QA metadata may or may not be present depending on whether or not the data granule was investigated for quality assessment. The metadata file should be examined to determine if post-production QA was applied to the granule (Riggs, Hall, and Salomonson 2003).

File Naming Convention

The following file naming convention is common to all Level 3 MODIS Land products: MOD10A2.A2003138.h03v06.005.2006.143062148.hdf

Refer to Table 1 for an explanation of the variables used in the MODIS file naming convention.

Table 1. Variable Explanation for MODIS File Naming Convention
Variable Explanation
MOD
MODIS/Terra
10A2
Type of product
A
Acquisition date
2003
Year of data acquisition
138
Day of year of data acquisition (In this case, day 138. The date in the granule is the first day of data in the eight-day file.)
h03v06
Horizontal tile number and vertical tile number. See the MODIS Sinusoidal Grid (SIN) as a reference.
005
Version number
2006
Year of production (2006)
143
Day of year of production (Day 143)
062148
Hour/minute/second of production in Greenwich Mean Time (GMT) (06:21:48)
hdf
HDF-EOS data forma

File Size

Data files are typically between 0.5 - 3 MB using HDF compression.

Note: New in V005, MOD10A2 data files now use HDF data compression. The extent to which compression reduces the file size varies from image to image, but generally it is a factor of 7 or more.

Spatial Coverage

Coverage is global, but only land tiles are produced for MOD10A2. The following resources can help you select and work with MOD10A2 tiles:

Latitude Crossing Times

The local equatorial crossing time of the Terra satellite is approximately 10:30 A.M. in a descending node with a sun-synchronous, near-polar, circular orbit.

Spatial Resolution

Gridded resolution is 500 m.

Projection

MOD10A1 V005 data are georeferenced to an equal-area sinusoidal projection. The following Web sites provide links to the software tools that either read data in a sinusoidal projection or convert sinusoidal to other projections:

In the sinusoidal projections, areas on the data grids are proportional to the same areas on the Earth, and distances are correct along all parallels and the central meridian. Shapes are increasingly distorted away from the central meridian and near the poles. Finally, the data are neither conformal, perspective, nor equidistant (USGS 2000).

Meridians are represented by sinusoidal curves (except for the central meridian), and parallels are represented by straight lines. The central meridian and parallels are straight lines of true scale (Pearson 1990). Specific parameters are listed in Table 2:

Table 2. Sinusoidal Projection Parameters
Earth radius
6371007.181000 meters
Projection origin
0° latitude, 0° longitude
Orientation
0° longitude, oriented vertically at top
Upper left corner point (m)
-20015109.354(x), 10007554.677(y)
Lower right corner point (m)
20015109.354(x), -10007554.677(y)
True scale (m)
463.31271653(x), 463.31271653(y)

Grid Description

Level-3 eight-day data are gridded in equal-area tiles. Each tile consists of a 1200 km by 1200 km data array, which corresponds to 2400 x 2400 pixels at 500 m resolution. The following image shows tile locations for MOD10A2 V005 data in a sinusoidal projection. Click on the thumbnail to view a larger image.

sinusoidal graph

Although this product is referred to as having a 500 m grid, the true pixel resolution is 463.31271653 m in both X and Y directions. Refer to Table 2. This allows for 2400 pixel by 2400 pixel tiles, each tile covering exactly 10 degrees of latitude vertically.

The MODIS MODLAND Tile Calculator converts between MODIS tile/image cooordinates or map coordinates in meters and latitude/longitude coordinates.

Temporal Coverage

MODIS data extends from 04 July 2002 to present.

Over the course of the Aqua mission, there have been a number of anomalies that have resulted in dropouts in the data. If you are looking for data for a particular date or time and can not find it, please visit the MODIS/Aqua Data Outages Web page.

Temporal Resolution

Temporal resolution is eight days, one half of the exact ground track repeat period of 16 days for the Terra satellite.

The eight-day periods begin on the first day of the year and extend into the next year. In some cases, there may not be eight days of input. You should check the Number of Input Days, Days Input, and Eight Day Period global attributes to find out what days are covered. See the Product Specific Global Attributes section of the MOD10A2 and MYD10A2 Global Attributes document for these global attributes. The product is only produced if at least two days of input are available for the eight-day period. The data file name indicates the first day in the eight-day period.

Table 3. Temporal Coverage
Period Days
------ -----
1 1-8
2 9-16
3 17-24
4 25-32
5 33-40
6 41-48
7 49-56
8 57-64
9 65-72
10 73-80
11 81-88
12 89-96
13 97-104
14 105-112
15 113-120
16 121-128
17 129-136
18 137-144
19 145-152
20 153-160
21 161-168
22 169-176
23 177-184
             
Period Days
------ -----
24 185-192
25 193-200
26 201-208
27 209-216
28 217-224
29 225-232
30 233-240
31 241-248
32 249-256
33 257-264
34 265-272
35 273-280
36 281-288
37 289-296
38 297-304
39 305-312
40 313-320
41 321-328
42 329-336
43 337-344
44 345-352
45 353-360
46 361-368*

Parameter or Variable

Parameter Description

The snow mapping algorithm classifies pixels as snow, snow-covered lake ice, cloud, water, land, or other. Maximum Snow Extent and Eight Day Snow Cover are the primary variables of interest in this data set.

Parameter Range

Refer to the MOD10A2 and MYD10A2 Local Snow Cover Attributes, Version 5 document for a key to the meaning of the coded integer values in the Maximum Snow Extent Field.

See Summary of MOD10A2/MYD10A2 Bit Values for an interpretation of bit values and resulting integer values for the Eight Day Snow Cover field.

4. Data Processing

Theory of Measurements

For more information regarding this topic, please see the Theory of Measurements section in the MODIS/Terra Snow Cover 5-Min L2 Swath 500m, Version 5 guide document (MOD10_L2).

Derivation Techniques and Algorithms

The MODIS science team is responsible for algorithm development. MODAPS is responsible for product generation and transfer of products to NSIDC.

Processing Steps

The algorithm first checks that the dates from MOD10A1 input data match those from the intended MOD10A2 time range, and then orders the data chronologically. Multiple days of observations for a cell are examined. If snow cover is found for any day, then the cell in the Maximum Snow Extent field is labeled as snow. If no snow is found, but there is one value that occurs more than once, that value is placed in the cell. For example, if a pixel is classified as water for five days, cloud for one day, land for one day, and night for one day, it would be ultimately labeled as water. If mixed observations occur, for example, land and cloud for more than one day in a given pixel, the algorithm assumes a cloud-free period and labels a pixel with the observed value. This logic minimizes cloud-cover extent, such that a cell needs to be cloud-obscured for all days in order to be labeled cloud. If all observations for a cell are analyzed but a classification cannot be determined, then that cell is labeled as no decision. A chronology of snow occurrence is recorded in the Eight Day Snow Cover field. The eight bits within a byte correspond to eight days of data. If snow is found in a pixel for a given day, the corresponding bit in the Eight Day Snow Cover field is set to a value of one (Riggs, Hall, and Salomonson 2003).

Error Sources

As with any upper level product, the characteristics of and/or anomalies in input data may carry through to the output data product. The following product is input to the algorithms used to create the MOD10A2 product:

Quality Assessment

Quality indicators for MODIS snow data can be found in the following places:

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 documents:

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 algorithm tests for a variety of anomalous conditions and sets the pixel value accordingly if such conditions are detected. Summary statistics about missing data, the percent cloud cover, the percent of good or other quality data, and snow cover percent are calculated and placed in the metadata for each product.

The NASA Goddard Space Flight Center: MODIS Land Quality Assessment Web site provides updated quality information for each product.

5. Data Acquisition

Sensor or Instrument Description

Principles of Operation

The MODIS instrument provides 12-bit radiometric sensitivity in 36 spectral bands, ranging in wavelength from 0.4 µm to 14.4 µm. Two bands are imaged at a nominal resolution of 250 m at nadir, five bands at 500 m, and the remaining bands at 1000 m. A ±55 degree scanning pattern at 705 km altitude achieves a 2330 km swath with global coverage every one to two days.

The scan mirror assembly uses a continuously rotating double-sided scan mirror to scan ±55 degrees, driven by a motor encoder built to operate 100 percent of the time throughout the six year instrument design life. The optical system consists of a two-mirror off-axis afocal telescope which directs energy to four refractive objective assemblies: one each for the visible, near-infrared, and longwave-infrared spectral regions (MODIS Web 2003).

Technical Specifications

Table 4. Technical Specifications
Orbit 705 km, 10:30 A.M. descending node (Terra)
Scan Rate 20.3 rp
Swath Dimensions 2330 km (cross track) by 10 km (along track at nadir)
Telescope 17.78 cm diameter off-axis, afocal (collimated) with intermediate field stop
Size 1.0 x 1.6 x 1.0 m
Weight 228.7 kg
Power 162.5 W (single orbit average)
Data Rate 10.6 Mbps (peak daytime); 6.1 Mbps (orbital average)
Quantization 12 bits
Spatial Resolution 250 m (bands 1-2)
500 m (bands 3-7)
1000 m (bands 8-36)
Design Life Six years


Spectral Bands

For information on the 36 spectral bands provided by the MODIS instrument, see the Spectral Bands Table.

Sensor or Instrument Measurement Geometry

The MODIS scan mirror assembly uses a continuously rotating double-sided scan mirror to scan ±55 degrees with a 20.3 rpm. The viewing swath is 10 km along track at nadir and 2330 km cross track at ±55 degrees.

Manufacturer of Sensor or Instrument

MODIS instruments were built to NASA specifications by Santa Barbara Remote Sensing, a division of Raytheon Electronics Systems.

Calibration

MODIS has a series of on-board calibrators that provide radiometric, spectral, and spatial calibration of the MODIS instrument. The blackbody calibrator is the primary calibration source for thermal bands between 3.5 µm and 14.4 µm, while the Solar Diffuser (SD) provides a diffuse, solar-illuminated calibration source for visible, near-infrared, and longwave infrared bands. The Solar Diffuser Stability Monitor (SDSM) tracks changes in the reflectance of the SD with reference to the sun so that potential instrument changes are not incorrectly attributed to changes in this calibration source. The Spectroradiometric Calibration Assembly (SRCA) provides additional spectral, radiometric, and spatial calibration.

MODIS uses the moon as an additional calibration technique and for tracking degradation of the SD by referencing the illumination of the moon since the moon's brightness is approximately the same as that of the Earth. Finally, MODIS deep space views provide a photon input signal of zero, which is used as a point of reference for calibration (MODIS Web 2003).

Data Acquisition Methods

Source or Platform Mission Objectives

MODIS is a key instrument aboard the Terra satellite, the flagship of NASA�s Earth Observing System (EOS). The EOS includes a series of satellites, a data system, and the world-wide community of scientists supporting a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans that together enable an improved understanding of the Earth as an integrated system. MODIS plays a vital role in the development of validated, global, and interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment (NASA's MODIS Web Site 2006), (NASA's Terra Web Site 2006), and (NASA's EOS Web Site 2006).

MODIS Snow and Sea Ice Global Mapping Project Objectives

Within this overall context, the objectives of the MODIS snow and ice team are to develop and implement algorithms that map snow and ice on a daily basis, and provide statistics of the extent and persistence of snow and ice over eight-day periods. Data at 500 m resolution enables sub-pixel snow mapping for use in regional and global climate models. A study of sub grid-scale snow-cover variability is expected to improve features of a model that simulates Earth radiation balance and land-surface hydrology.

Data Collection System

The MODIS sensor contains a system whereby visible light from the earth passes through a scan aperture and into a scan cavity to a scan mirror. The double-sided scan mirror reflects incoming light onto an internal telescope, which in turn focuses the light onto four different detector assemblies. Before the light reaches the detector assemblies, it passes through beam splitters and spectral filters that divide the light into four broad wavelength ranges. Each time a photon strikes a detector assembly, an electron is created. Electrons are collected in a capacitor where they are eventually transferred into the preamplifier. Electrons are converted from an analog signal to digital data, and downlinked to ground receiving stations (MODIS Web 2003).

Data Acquisition and Processing

The EOS Ground System (EGS) consists of facilities, networks, and systems that archive, process, and distribute EOS and other NASA earth science data to the science and user community. For example, ground stations provide space to ground communication. The EOS Data and Operations System (EDOS) processes telemetry from EOS spacecraft and instruments to generate Level-0 products, and maintains a backup archive of Level-0 products (ESDIS 1996). The NASA Goddard Space Flight Center: MODIS Adaptive Processing System (MODAPS) Services is currently responsible for generation of Level-1A data from Level-0 instrument packet data. These data are then used to generate higher level MODIS data products, including MOD10A2. MODIS snow and sea ice products are archived at the NSIDC Distributed Active Archive Center (DAAC) and distributed to EOS investigators and other users via external networks and interfaces (MODIS Web 2003). Data are available to the public through a variety of interfaces.

6. References and Related Publications

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, Dorothy K., George A. Riggs, and Vincent 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. <http://modis-snow-ice.gsfc.nasa.gov/?c=atbd&t=atbd> .

Hall, Dorothy K. and J. Martinec. 1985. Remote Sensing of Ice and Snow. London: Chapman and Hall.

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., J. L. Foster, Vincent 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, 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.

Klein, A. MODIS Snow Albedo Prototype. 2003. <http://geog.tamu.edu/klein/modis_albedo/> Accessed July 2003.

Klein, A. G. and Julienne Stroeve. 2002. Development and Validation of a Snow Albedo Algorithm for the MODIS Instrument. Annals of Glaciology 34:45-52.

Klein, A. G., Dorothy K. Hall, and George 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 Multispectral Scanner (MSS) and Thematic Mapper (TM) Post-Calibration Dynamic Ranges, Exoatmospheric Reflectances and At-Satellite Temperatures. EOSAT Technical Notes 1:3-8.

MODIS Characterization 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. January 2006. MODIS Snow Products User Guide for Collection 4 Data Products. <http://modis-snow-ice.gsfc.nasa.gov/sug_main.html>.

United States Geological Survey. "Sinusoidal Equal Area." Map Projections. 2003. <http://mac.usgs.gov/mac/isb/pubs/MapProjections/projections.html#sinusoidal> Accessed December 2000.

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.

7. Document Information

Acronyms and Abbreviations

The following acronyms and abbreviations are used in this document:

Table 5. Acronyms and Abbreviations
ATBD Algorithm Theoretical Basis Document
DAAC Distributed Active Archive Center
EDOS EOS Data and Operations System
EGS EOS Ground System
EOS Earth Observing System
EOSDIS Earth Observing System Data and Information System
ESDIS Earth Science Data and Information System
FTP File Transfer Protocol
GMT Greenwich Mean Time
GSFC Goddard Space Flight Center
HDF-EOS Hierarchical Data Format - Earth Observing System
MCST MODIS Characterization Support Team
MODIS Moderate Resolution Imaging Spectroradiometer
MODLAND MODIS Land Discipline Group
MSS Multispectral Scanner
NASA National Aeronautics and Space Administration
NCSA National Center for Supercomputing Applications
NDSI Normalized Difference Snow Index
NSIDC National Snow and Ice Data Center
QA Quality Assessment
SD Solar Diffuser
SDP Science Data Processing
SDS Scientific Data Set
SDSM Solar Diffuser Stability Monitor
SIN Sinusoidal Grid
SRCA Spectroradiometric Calibration Assembly
TM Thematic Mapper

Document Creation Date

February 2004

Document Revision Date

December 2006

Document URL

http://nsidc.org/data/docs/daac/modis_v5/mod10a2_modis_terra_snow_8-day_global_500m_grid.gd.html