MODIS/Terra Sea Ice Extent Daily L3 Global 1km EASE-Grid Day, Version 5


The MODIS/Terra Sea Ice Extent Daily L3 Global 1km EASE-Grid Day (MOD29P1D) data set contains fields for Sea Ice by Reflectance, Sea Ice by Reflectance Spatial QA, Ice Surface Temperature (IST), and Ice Surface Temperature Spatial QA in Hierarchical Data Format-Earth Observing System (HDF-EOS) format along with corresponding metadata. The fields Sea Ice by IST and Combined Sea Ice that were in Version 4 (V004) were removed from Version 5 (V005). MOD29P1D V005, the latest version of the Moderate Resolution Imaging Spectroradiometer (MODIS) data, consists of 954 km x 954 km tiles of 1 km resolution data gridded in the Lambert Azimuth Equal Area map projection. 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.

Citing These Data

As a condition of using these data, you must cite the use of this data set 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. 2006, updated daily. MODIS/Terra Sea Ice Extent Daily L3 Global 1km EASE-Grid Day 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 the sea ice algorithm applies only to ocean pixels. Gridded resolution is 1 km.
Temporal coverage and resolution MODIS data extends from 24 February 2000 to present. Temporal resolution is daily.
Tools for accessing and analyzing data MODIS: MODLAND Tile Calculator
HEG HDF-EOS to GeoTIFF Conversion Tool
Space Science and Engineering Center (SSEC): Terra Orbit Tracks GLOBAL
NSIDC's Hierarchical Data Format - Earth Observing System (HDF-EOS) site
HDF Java Products: NCSA HDFView
MODIS Rapid Response System
NASA Goddard Space Flight Center: MODIS Land Global Browse Images
The MODIS Conversion Toolkit (MCTK)
Data range
Sea Ice by Reflectance Field Coded Integer Values
Value Description
missing data
no decision
inland water
sea ice
land mask
ocean mask
Ice Surface Temperature (IST) Field Scaled Values
Value (after scaling) Description
no decision
inland water
open ocean
243.0 - 273.0
expected IST range

For more information regarding the scaled value and the coded integer value descriptions, please see the MOD29P1D and MYD29P1D Local Sea Ice Attributes, Version 5 document.
Grid type and size MOD29P1D data are gridded to Equal Area Scalable Earth Grid (EASE-Grid) tiles, 951 x 951 pixels in size.
File naming convention Example: MOD29P1D.A2000057.h04v06.005.2006252042343.hdf
File size 0.05 -1.5 MB using HDF compression
Parameter(s) Sea Ice by Reflectance
Ice Surface Temperature (IST)
Procedures for obtaining data

Reverb: NASA search and order tool for subsetting, reprojecting, and reformatting data.
Subscription Service: Subscribe to have new data automatically sent when the data become available.

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)
Mail stop 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
Science Systems and Applications, Inc.
Mail stop 614.1
Greenbelt, MD 20771

Technical Contact

NSIDC User Services
National Snow and Ice Data Center
University of Colorado
Boulder, CO 80309-0449  USA
phone: +1 303.492.6199
fax: +1 303.492.2468
form: Contact NSIDC User Services

2. Data Access and Tools

Data Access Aids

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

Data Access Tools

Data are available via the following methods:
Reverb: NASA search and order tool for subsetting, reprojecting, and reformatting data.
Subscription Service: Subscribe to have new data automatically sent when the data become available.

Data Analysis Tools

The following software tools can help you analyze the data:

3. Detailed Data Description

Algorithms that generate sea ice 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 latest version available, which is the highest version number. Version 5 (V005) is the most current version of MODIS data available from NSIDC. For V005, the Science Data Sets Sea Ice by Ice Surface Temperature and Combined Sea Ice present in Version 4 (V004) were deleted from the product.

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


MODIS sea ice products are archived in compressed HDF-EOS version 2.9 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 from Reverb | ECHO, NASA's Next Generation Earth Science Discovery Tool.

MOD29P1D consists of 951 x 951 cells of tiled data in the Lambert Azimuth Equal Area 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 global attributes and HDF-predefined fields, which are stored with their associated SDS.

Description of Data Fields

External Metadata File

A separate ASCII text file containing metadata with a .xml file extension accompanies the HDF-EOS file. This ASCII text file contains some of the same metadata as in the HDF-EOS file, but also includes other information regarding archiving, user support, and post production QA relative to the granule ordered. The post-production QA metadata may or may not be present in the .xml file depending on whether or not the data granule was investigated for Quality Assessment. The ASCII text file should be examined to determine if post-production QA was applied to the granule (Riggs, Hall, and Salomonson 2006).

File Naming Convention

The file naming convention used for the MOD29P1D product is MOD29P1D.A2000057.h04v06.005.2006252042343.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
Type of product
Acquisition date
Year of data acquisition
Day of year of data acquisition (day 57)
Horizontal tile number and vertical tile number. For further information, see the
Grid Description section in this document.
Version number
Year of production (2006)
Day of year of production (day 252)
Hour/minute/second of production in GMT (04:23:43)
HDF-EOS data format

File Size

Data files are typically between 0.05 - 1.5 MB using HDF compression.

Note: New in V005, MOD20P1D 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 5 or more.

Spatial Coverage

Coverage is global; however, only ocean granules are produced. A ±55 degree scanning pattern at a 705 km altitude achieves a 2330 km swath with global coverage every one to two days. The following resources can help you select and work with MOD29P1D 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 1 km.


MOD29P1D data are gridded to the NSIDC EASE-Grid, a Lambert Azimuthal Equal Area Projection. Please review All About EASE-Grid Web page for general information on the EASE-Grid.

The following Web sites provide links to the software tools that reformat, re-project, and perform stitching/mosaicing, and subsetting operations on HDF-EOS objects:

In the polar aspect of the Lambert Azimuthal Equal Area Projection, all meridians are straight lines and all parallels are circles with either the north or south pole as the center of the projection (Snyder 1987). Areas on the map are shown in true proportion to the same areas on the Earth. Directions are true only from the pole. Scale decreases gradually away from the pole. Distortion of shapes increases away from the pole. Any straight line drawn through the pole is on a great circle. Finally, the map is equal area but neither conformal, perspective, nor equidistant (USGS 2003). Specific parameters are listed in Table 2.

Table 2. Lambert Azimuthal Equal Area Map Projection Parameters
Earth radius
6371228.0 meters
Projection origin
North (90° latitude, 0° longitude)
South (-90° latitude, 0° longitude)
North (0° longitude, oriented vertically at bottom)
South (0° longitude, oriented vertically at top)
Upper left corner point (m)
-9058902.1845(x), 9058902.1845(y)
Lower right corner point (m)
9058902.1845(x), -9058902.1845(y)
True scale (m)
1002.7010(x), 1002.7010(y)

Grid Description

MOD29P1D data are gridded to Polar EASE-Grid tiles, each 951 x 951 pixels in size, which corresponds to approximately 954 km by 954 km at a resolution of 1002.7010 m per pixel.

The following maps show tile locations for MOD29P1D. Click on the thumbnail images to see the full-resolution images.

EASE-Grid tiles, Northern Hemisphere
EASE-Grid tiles, Southern Hemisphere

See the following documents for bounding coordinate information for each tile:

Temporal Coverage

MODIS data extends from 24 February 2000 to present. The time between repeat coverage of a given point on the earth depends on latitude with the most frequent coverage occurring near the poles. Areas poleward of ±30 degrees latitude are observed at least daily.

Over the course of the Terra 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/Terra Data Outages Web page.

Temporal Resolution

Temporal resolution is daily.

Parameter or Variable

Parameter Description

The sea ice algorithm classifies pixels as sea ice, cloud, open ocean, inland water, or land. In the Sea Ice by Reflectance field, sea ice is distinguished from open water based on reflective properties. In the IST field, pixels classified as sea ice contain an IST value in kelvins, and pixel values are scaled by 100 for all classes. The IST algorithm was designed for sea ice; however, IST values are provided for areas over open ocean.

Parameter Range

Refer to the MOD29P1D and MYD29P1D Local Sea Ice Attributes, Version 5 document for a key to the meaning of the coded integer values in the Sea Ice by Reflectance Field and Ice Surface Temperature Field.

4. Data Processing

Theory of Measurements

For information regarding the theory for sea ice mapping and ice suface temperature retrieval, please see the Theory of Measurements section in the MODIS/Terra Sea Ice Extent 5-Min L2 Swath 1km, Version 5 guide document (MOD29).

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

For more information regarding the processing steps used as the input to this data set, please see the Processing Steps section in the MODIS/Terra Sea Ice Extent 5-Min L2 Swath 1km, Version 5 guide document (MOD29).

The sea ice algorithm selects an observation of the day from multiple observations mapped to a MOD29GD grid cell. A scoring algorithm selects the most favorable observation of the day based on the MOD29GD derived solar elevation, observation coverage in a grid cell, and distance from nadir. The objective is to select observations that are near nadir, acquired near noon local time, and have a large coverage area in a grid cell. This algorithm applies to daytime reflectance data. In day mode, MODIS collects both visible and thermal data. The scoring algorithm uses the visible data to determine the observation of the day for reflectance and thermal data. The score for each observation is given by the following formula:

score = (0.5x solar elevation) + (0.3x observation coverage) + (0.2x distance from NADIR)

The observation with the highest score for a grid cell is selected as the observation for the day. The thermal observation corresponding to the visible observation is the IST observation of the day (Riggs, Hall, and Salomonson 2006).

Error Sources

As with any upper level product, the characteristics of or anomalies in input data may carry through to the output data product. The following products are input to MYD29P1D:

Quality Assessment

All MODIS/Aqua sea ice products are considered validated 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:

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:

The ScienceQualityFlag and the ScienceQualityFlagExplanation may be 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. A sampling of products will be inspected. Random sampling or support of specific events, such as field campaigns, may also be conducted.

The IST Spatial QA and Sea Ice by Reflectance Spatial QA data fields provide additional information on algorithm results for each pixel within a spatial context, and are used as a measure of usefulness for sea ice data. 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).

See the MODIS Land Quality Assessment Web page for further details.

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 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, shortwave-infrared, and longwave-infrared spectral regions (MODIS Web 2003).

Technical Specifications

Table 3. MODIS Instrument Technical Specifications
Orbit 705 km, 1:30 p.m. ascending node (Aqua), sun-synchronous, near-polar, circular
Scan Rate 20.3 rpm, cross track
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 cross track. 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.


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 shortwave 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 Aqua satellite, one component 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 is playing 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 Aqua 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. 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 MODIS Adaptive Processing System (MODAPS) 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 MYD29. MODIS snow and 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

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, D. 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 Ssing 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. <> .

Hapke, B. 1993. Theory of Reflectance and Emittance Spectroscopy. Cambridge: Cambridge University Press.

Key, Jeffrey R., J. B. Collins, C. Fowler, and R. S. Stone. 1997. High Latitude Surface Temperature Estimates From Thermal Satellite Data. Remote Sensing of the Environment 61:302-309.

Key, Jeffrey 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. <> 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. December 2006. MODIS Sea Ice Products User Guide to Collection 5. PDF.

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.

Snyder, John P. 1987. Map Projections: a Working Manual. U. S. Geological Survey Professional Paper 1395. Department of the Interior. Washington, D. C.

United States Geological Survey. 2003. Lambert Azimuthal Equal Area Map Projections. Accessed April 2007.

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 4. Acronyms and Abbreviations
ATBD Algorithm Theoretical Basis Document
AVHRR Advanced Very High Resolution Radiometer
DAAC Distributed Active Archive Center
EASE-Grid Equal Area Scalable Earth Grid
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
IST Ice Surface Temperature
LP DAAC Land Processes Distributive Active Archive Center
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
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
SRCA Spectroradiometric Calibration Assembly
TM Thematic Mapper

Document Creation Date

February 2004

Document Revision Date

January 2007

Document URL