All MODIS Version 6.1 data products from 7 July 2023 onward may be subject to more frequent non-recoverable data loss due to the Flight Operation Team (FOT) transition to Lights-Out-Operations (LOOps). Please see our website for further details and updates.
On Wednesday, November 29, from 9:00 a.m. to 2:30 p.m. (US Mountain Time), the following data collections may not be available due to planned system maintenance: ASO, AMSR Unified, AMSR-E, Aquarius, High Mountain Asia, IceBridge, ICESat/GLAS, ICESat-2, LVIS, MEaSUREs, MODIS, Nimbus, SMAP, SnowEx, SSM/I-SSMIS and VIIRS.
MODIS/Aqua Snow Cover 8-Day L3 Global 500m SIN Grid, Version 61
Data set id:
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COMPREHENSIVE Level of Service
Data: Data integrity and usability verified; data customization services available for select data
Documentation: Key metadata and comprehensive user guide available
User Support: Assistance with data access and usage; guidance on use of data in tools and data customization services
This is the most recent version of these data. Version Summary
1. The low visible reflectance screen for snow cover using bands 2 and 4 was lowered from 0.10 to 0.07. 2. Cloud mask algorithm flags are set for 'probably cloudy' and 'probably clear' sky conditions in the algorithm flags QA data set.
In this section
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This global Level-3 (L3) data set provides the maximum snow cover extent (SNE) observed over an eight-day period within 10° x 10° MODIS sinusoidal grid tiles. Tiles are generated by compositing 500 m observations from the 'MODIS/Aqua Snow Cover Daily L3 Global 500m Grid' data set (DOI:10.5067/MODIS/MYD10A1.061). A bit flag index is used to track the eight-day snow/no-snow chronology for each 500 m cell.
The terms "Version 61" and "Collection 6.1" are used interchangeably in reference to this release of MODIS data.
4 July 2002 to present
Blue outlined yellow areas on the map below indicate the spatial coverage for this data set.
Programmatically request selected data products through our API. This tool is valuable for selecting just the parameters you need from big data sets. Apply spatial and temporal filters, subsetting, reformatting, and reprojection.
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Data products from VIIRS are created to be similar to MODIS data products to ensure the continuity needed for the development of snow and sea ice climate records beyond the life expectancy of MODIS. The temporal resolution and spatial extent are identical in MODIS and VIIRS.
The lag time between observations and availability of MODIS products is only a few days. Lag time may be extended due to satellite maneuvers and extra quality assurance required for the geolocation data after the maneuver.
The Normalized Difference Snow Index (NDSI) snow cover is an index that is related to the presence of snow in a pixel and is a more accurate description of snow detection as compared to Fractional Snow Cover (FSC). Snow typically has very high visible (VIS) reflectance and very low reflectance in
Many NSIDC DAAC data sets can be accessed using the NSIDC DAAC's Data Access Tool. This tool provides the ability to search and filter data with spatial and temporal constraints using a map-based interface.
Users have the option to
To convert HDF5 files into binary format you will need to use the h5dump utility, which is part of the HDF5 distribution available from the HDF Group. How you install HDF5 depends on your operating system.
Data subscriptions are available for select NSIDC DAAC data collections. Once signed up, the subscription service automatically sends you new data as they are delivered from active NASA satellite missions.
All data from the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) can be accessed directly from our HTTPS file system, using wget or curl. Basic command line instructions are provided in the article below.
NASA Earthdata Search is a map-based interface where a user can search for Earth science data, filter results based on spatial and temporal constraints, and order data with customizations including re-formatting, re-projecting, and spatial and parameter subsetting.