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Description

The MCD12C1 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the MCD12C1 Version 6.1 data product.

The Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) (MCD12C1) Version 6 data product provides a spatially aggregated and reprojected version of the tiled MCD12Q1 Version 6 data product. Maps of the International Geosphere-Biosphere Programme (IGBP), University of Maryland (UMD), and Leaf Area Index (LAI) classification schemes are provided at yearly intervals at 0.05 degree (5,600 meter) spatial resolution for the entire globe from 2001 to 2020. Additionally, sub-pixel proportions of each land cover class in each 0.05 degree pixel is provided along with the aggregated quality assessment information for each of the three land classification schemes.

Provided in each MCD12C1 Version 6 Hierarchical Data Format 4 (HDF4) file are layers for Majority Land Cover Type 1-3, Majority Land Cover Type 1-3 Assessment, and Majority Land Cover Type 1-3 Percent.

Known Issues

Improvements/Changes from Previous Version

  • Updated to include the improvements and changes made for the MCD12Q1 Version 6 data product.
  • Version 6 does not include a Majority Land Cover Type Quality Control (QC) Layer.
  • Land_Cover_Type_Percent_1, Land_Cover_Type_Percent_2, Land_Cover_Type_Percent_3 layers have up to 17 dimensions and include the sub-pixel proportions of the IGBP, UMD, and LAI classes in each 0.05 degree pixel.
  • The IGBP classification scheme legend used differs from the legend used for the MCD12Q1 Version 6 data product and can be found on page 16 of the User Guide.
  • The data product should not be used to determine post-classification land cover change between years due to the uncertainty in the land cover labels for any one year. More information can be found on page 2 of the User Guide.

Version Description

The MCD12C1 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the MCD12C1 Version 6.1 data product (https://doi.org/10.5067/MODIS/MCD12C1.061).

Product Summary

Platforms
Terra,
Aqua
Instruments
MODIS
Spatial Extent
N: 90 S: -90 E: 180 W: -180
Spatial Resolution
5600 Meters x 5600 Meters
Geographic Region
GLOBAL
Coordinate System
CARTESIAN
Granule Spatial Representation
CARTESIAN
Temporal Extent
2001-01-01 to 2020-12-31
Temporal Resolution
1 Year
Data Partner
Land Processes Distributed Active Archive Center (LP DAAC)
MODIS Adaptive Processing System, Terrestrial Information Systems Laboratory, Earth Sciences Division, Science and Exploration Directorate, Goddard Space Flight Center, NASA (NASA/GSFC/SED/ESD/TISL/MODAPS)
Concept ID
C2763289440-LPCLOUD
Data State
DEPRECATED
Processing Level
3
Published
Updated
Science Keywords
Land Use/Land Cover Classification

Citation

Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.

Copy Citation

Friedl, M., & Sulla-Menashe, D. (2015). MCD12C1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V006 [Data set]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/MODIS/MCD12C1.006 Date Accessed: 2025-10-22

File Naming Convention

MCD12C1.A2003001.006.2018053185458.hdf

The file name begins with the Product Short Name (MCD12C1) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2003001), the Version of the data collection (006), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2018053185458), and the Data Format (hdf).

Documents

Publications Citing This Dataset

Filters
Title Year Author
Accuracy, stability, and continuity of AVHRR, SeaWiFS, MODIS, and VIIRS deep blue long-term land aerosol retrieval in Asia Su, X.
Global patterns and ecological implications of diurnal hysteretic response of ecosystem water consumption to vapor pressure deficit Xu, X.
Regional scale analysis of land cover dynamics in Kerala over last two decades through MODIS data and statistical techniques H, V.
Global land cover mapping using annual clear-sky composites from FY3D/MERSI-II Wang, Y. Y.
Uncertainties in partitioning evapotranspiration by two remote sensing-based models Chen, H.
Pronounced loss of Amazon rainforest resilience since the early 2000s Boulton, C. A.
Interactive effects on habitat quality using InVEST and GeoDetector models in Wenzhou, China Zhang, X.
Long-term vegetation phenology changes and responses to preseason temperature and precipitation in northern China Zhang, R.
Greater temperature sensitivity of vegetation greenup onset date in areas with weaker temperature seasonality across the Northern Hemisphere Shen, M.
Effect of shrub encroachment on land surface temperature in semi-arid areas of temperate regions of the Northern Hemisphere Shen, X.
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Variables

Variables are a set of physical properties whose values determine the characteristics or behavior of something. For example, temperature and pressure are variables of the atmosphere. Parameters and variables can be used interchangeably. Variable level attributes provide individual information for each variable.

The Name in this table is the variable name. Fill value indicates missing or undefined data points in a variable. Valid range is the range of values the variable can store. Scale factor is used to increase or decrease the size of an object and can be used to correct for distortion. For questions on a specific variable, please use the Earthdata Forum.

Name Description Units Data Type Fill Value Valid Range Scale Factor
Land_Cover_Type_1_Percent Percent cover of each IGBP class at each pixel Percent uint8 255 255 to 100 N/A
Land_Cover_Type_2_Percent Percent cover of each UMD class at each pixel Percent uint8 255 255 to 100 N/A
Land_Cover_Type_3_Percent Percent cover of each LAI class at each pixel Percent uint8 255 255 to 100 N/A
Majority_Land_Cover_Type_1 Most likely IGBP class for each 0.05 degree pixel Class uint8 255 255 to 16 N/A
Majority_Land_Cover_Type_1_Assessment Majority IGBP class confidence Percent uint8 255 255 to 100 N/A
Majority_Land_Cover_Type_2 Most likely UMD class for each 0.05 degree pixel Class uint8 255 255 to 15 N/A
Majority_Land_Cover_Type_2_Assessment Majority UMD class confidence (filled with land/water mask) Percent uint8 255 255 to 100 N/A
Majority_Land_Cover_Type_3 Most likely LAI class for each 0.05 degree pixel Class uint8 255 255 to 10 N/A
Majority_Land_Cover_Type_3_Assessment Majority LAI class confidence (filled with land/water mask) Percent uint8 255 255 to 100 N/A
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