Full catalog/MCD12Q1
MCD12Q1·v061·dataset

What covers the land: forest, city, water (Terra+Aqua, yearly, 500 m)

MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid V061
land NASA LPCLOUD Level 3 active HDF-EOS2
In plain English

What it measures. A yearly map of what covers the land in each 500 m patch, sorted into categories like forest, grassland, cropland, city, water, and more, using several different classification schemes.

How it's made. Created by combining reflectance data from the MODIS sensors on Terra and Aqua and running it through trained classification software, with extra post-processing to refine the categories.

How & where you'd use it. Widely used to track land use and land-cover change over the years, and as a foundational map for environmental, hydrology, and climate studies.

What's measured

LAND SURFACE › LAND USE/LAND COVER › LAND USE/LAND COVER CLASSIFICATION

Coverage & cadence

  • Time span2001-01-01 → ongoing
  • Measured byTerra (MODIS) · Aqua (MODIS)
  • Processing levelLevel 3
  • Spatial extent-180, -90, 180, 90
  • FormatsHDF-EOS2
  • StatusACTIVE

What you can do with it

  • Track deforestation, fire scars and land-cover change
  • Monitor crop and vegetation health (NDVI/EVI)
  • Map how built-up vs. green an area is over time
Official description

The Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type (MCD12Q1) Version 6.1 data product provides global land cover types at yearly intervals. The MCD12Q1 Version 6.1 data product is derived using supervised classifications of MODIS Terra and Aqua reflectance data. Land cover types are derived from the International Geosphere-Biosphere Programme (IGBP), University of Maryland (UMD), Leaf Area Index (LAI), BIOME-Biogeochemical Cycles (BGC), and Plant Functional Types (PFT) classification schemes. The supervised classifications then undergo additional post-processing that incorporate prior knowledge and ancillary information to further refine specific classes. Additional land cover property assessment layers are provided by the Food and Agriculture Organization (FAO) Land Cover Classification System (LCCS) for land cover, land use, and surface hydrology. Layers for Land Cover Type 1-5, Land Cover Property 1-3, Land Cover Property Assessment 1-3, Land Cover Quality Control (QC), and a Land Water Mask are provided in each MCD12Q1 Version 6.1 Hierarchical Data Format 4 (HDF4) file. Known Issues * The "units" field is missing in the metadata, however, this information can be found in Table 1 of the User Guide. * The MCD12Q1.061 land cover data product is derived using supervised classification of MODIS Terra and Aqua reflectance data. The classification algorithm uses labeled training samples selected globally to represent land cover categories derived under the IGBP, UMD, LAI, BIOME-BGC, and PFT classification schemes. These training samples were selected to represent land classes, best suited over a certain period. However, due to lack of funding, the science team was not able to keep the training database updated over the course of the years, and some of these training sites could well have undergone changes in their land cover characteristics, especially after 2021. Hence users are urged to maintain caution while using the V6.1/MCD12Q1 land cover layers for 2021 and beyond. More information on this known issue can be found in the [Land Data Products Operational Products (LDOPE) Quality Assessment](https://landweb.modaps.eosdis.nasa.gov/displayissue?id=781). * Known issues are described in Section 2.2 of the User Guide. * For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=TerraAqua&as=61).

Get the data

mcd12q1_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="MCD12Q1",
    version="061",
    bounding_box=(-122.5, 37.2, -121.8, 37.9),  # your area (W,S,E,N)
    temporal=("2024-01-01", "2024-12-31"),       # your dates
)
files = earthaccess.open(results)   # stream straight from LPCLOUD
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.