Snow cover from MODIS data
- Coverage, spatial and temporal resolution
- Data quality
- Contact person
- Data citation
RESTRICTED:This link to the data set is only available for a restricted user group. The data set is only accessible in CEN/MPI net or accessible from external nets with a customer account. Please contact ICDC if you would like to access this data from outside the network.
- View MODIS snow cover data at LAS: AQUA TERRA
- Access MODIS AQUA and TERRA snow cover data via OPeNDAP
- Data access via file system (AQUA): /data/icdc/ice_and_snow/modis_aqua_snowcover
- Data access via file system (TERRA): /data/icdc/ice_and_snow/modis_terra_snowcover
Reflectance and radiance observations obtained with the Moderate Resolution Imaging Spectroradiometer (MODIS) at its bands 4 ( 0.55µm) and 6 (1.6µm) can be used to calculate the Normalized Difference Snow Index (NDSI) which is a measure of the snow cover at the surface.
This NDSI can be used together with a regression to obtain the fractional snow cover (FSC). The data offered here belong to MODIS Collection 6.1 and are available for both satellites: Terra and Aqua. For this newest release of the MODIS snow cover data set the regression is not applied (unlike done in Collection 005) for reasons detailed in the MODIS Collection 6.1 snow cover Users Guide (see references). Users are invited to compute the FSC on their own by taking the regression from the ATBD (see references).
Influence of vegetation, sensor viewing angle, solar illumination, and clouds are taken into account. Collection 6.1 snow cover data benefit from a number of revisions to both input data and algorithm design as described in the Users Guide. More details can be found in the documents listed in the references listed below.
Last update of data set at ICDC: February 3, 2022
|NDSI snow cover||%||monthly, daily|
|Percentage clear-sky fraction||%||daily|
|Percentage cloud fraction||%||daily|
|Quality flag||none||monthly, daily|
Period and temporal resolution:
- Monthly: 2000-03 (Terra) or 2002-09 (Aqua) to 2021-12
- Daily: 2000-02-24 (Terra) or 2002-07-04 (Aqua) to 2021-12-31
Coverage and spatial resolution:
- Spatial resolution: 0.05° x 0.05°, cartesian grid
- Geographic latitude: -89.975°N to 89.975°N
- Geographic longitude: -179.975°E to 179.975°E
- Dimension: 7200 columns x 3600 rows
- Altitude: following terrain
- NetCDF (at ICDC)
- HDF (at NSIDC)
The quality flags included in the data set give qualitative information about the quality of the NDSI snow cover retrieval (very good, good, ok, ...). In addition these flags inform about the cloud cover; particularly the latter is important for the monthly product because it does not contain separate maps about cloud cover like the daily product does. The quality flags are included in both the daily and monthly product but are more detailed in the daily one.
The daily product contains in addition maps about the percentage clear-sky fraction and about the percentage cloud fraction. This information has to be taken into account when interpreting the snow cover product. A retrieval of the NDSI is only possible in clear-sky areas.
More information about data quality and limitations of use are given in the references, particularly the Users Guide.
Some time periods are missing in the monthly data of Terra:
- 2000/08; 2001/06+07; 2002/03; 2003/12; 2016/02
Some time periods are missing in the daily data of Terra:
- 20000806-17; 20010616-0702;30; 20020320-27; 20020415; 20031217-23; 20081221+22; 20160219-27
and of Aqua:
- 20020730+31; 20020801-07; 20020913
ICDC / CEN / University of Hamburg
email: stefan.kern (at) uni-hamburg.de
NSIDC User Services
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO 80309-0449
email: nsidc (at) nsidc.org
- Algorithm Theoretical Basis Document (ATBD) for the MODIS Snow and Sea Ice-Mapping Algorithms
- Riggs, G. A., et al., Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records. Earth Syst. Sci. Data, 9, 765-777, https://doi.org/10.5194/essd-9-765-2017, 2017.
- Riggs, G. A., et al., MODIS Snow Products Collection 6.1 User Guide, Version 1.0, April 2019, 66 pp. (pdf, not barrier free)
- Masson, T., et al., 2018, An assessment of existing methodologies to retrieve snow cover fraction from MODIS data. Remote Sensing, 10(4), 619, http://doi.org/10.3390/rs10040619.
- 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. Rem. Sens. Environ., 66, 129-137.
- Hall, D. K., and G. A. Riggs, 2011, Normalized-difference snow index (NDSI). Encyclopedia of Earth Sciences Series, Encyclopedia of Snow, Ice and Glaciers, doi:10.1007/978-90-481-2642-2_376. http://doi.org/10.1007/978-90-481-2642-2_376
- Salomonson, V. V., and I. Appel, 2004, Estimating fractional snow cover from MODIS using the normalized difference snow index (NDSI). Rem. Sens. Environ., 89, 351-360.
- Salomonson, V. V., and I. Appel, 2006, Development of the AQUA MODIS NDSI fractional snow cover algorithm and validation results. Trans. Geosci. Rem. Sens., 44(7), 1747-1756.
- Nolin, A. W., 2010, Recent advances in remote sensing of seasonal snow. J. Glaciol., 56(200), 1141-1150.
- Xin, Q., et al., 2012, View angle effects on MODIS snow mapping in forests. Rem. Sens. Environ., 118, 50-59. (pdf, not barrier free)
Please cite the data as follows:
Hall, D. K. and G. A. Riggs. 2021. MODIS/Terra Snow Cover Daily L3 Global 0.05Deg CMG, Version 61. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/MODIS/MOD10C1.061 [last accessed: January 18, 2022], provided in netCDF file format by the Integrated Climate Data Center (ICDC), CEN, University of Hamburg, Hamburg, Germany.
If the monthly instead of the daily data are used, then please replace "Daily" by "Monthly" and "MOD10C1" by "MOD10CM".
If the Aqua MODIS data are used replace "Terra" by "Aqua" and "MOD" by "MYD".
and with the following acknowledgments:
Thanks to ICDC, CEN, University of Hamburg for data support.