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 underwent 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 also provided. Documentation: User's Guide Algorithm Theoretical Basis Document (ATBD) General Documentation

The MCD12Q1 V6 product provides global land cover types at yearly intervals (2001-2016) derived from six different classification schemes. It is derived using supervised classifications of MODIS Terra and Aqua reflectance data. The supervised classifications then undergo additional post-processing that incorporate prior knowledge and ancillary information to further refine specific classes.

The band selected in this dataset is the LC_Prop1 which represents the FAO-Land Cover Classification System 1 (LCCS1) land cover layer. The LC_Prop1 Class Table is provided by Google Earth Engine website at https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MCD12Q1#bands

Citation:

Please visit LP DAAC 'Citing Our Data' page for information on citing LP DAAC datasets

Contact points:

Resource Contact: NASA LP DAAC at the USGS EROS Center

Metadata Contact: FAO-Data

Resource constraints:

MODIS data and products acquired through the LP DAAC have no restrictions on subsequent use, sale, or redistribution.

Online resources:

LPDAAC-USGS (NASA Earth Data) Website onMODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500 m SIN Grid

Earth Engine Data Catalog

The NLCD-MODIS land cover-albedo database integrates high-quality MODIS albedo observations with areas of homogeneous land cover from NLCD. The spatial resolution (pixel size) of the database is 480m-x-480m aligned to the standardized UGSG Albers Equal-Area projection. The spatial extent of the database is the continental United States. This dataset is associated with the following publication: Wickham , J., C.A. Barnes, and T. Wade. Combining NLCD and MODIS to Create a Land Cover-Albedo Dataset for the Continental United States. REMOTE SENSING OF ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 170(0): 143-153, (2015).

These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MCD12Q1 The MODIS Land Cover Type product contains multiple classification schemes, which describe land cover properties derived from observations spanning a year's input of Terra and Aqua data. The primary land cover scheme identifies 17 land cover classes defined by the International Geosphere Biosphere Programme (IGBP), which includes 11 natural vegetation classes, 3 developed and mosiacked land classes, and three non-vegetated land classes. The MODIS Terra + Aqua Land Cover Type Yearly L3 Global 500 m SIN Grid product incorporates five different land cover classification schemes, derived through a supervised decision-tree classification method: Land Cover Type 1: IGBP global vegetation classification schemeLand Cover Type 2: University of Maryland (UMD) schemeLand Cover Type 3: MODIS-derived LAI/fPAR schemeLand Cover Type 4: MODIS-derived Net Primary Production (NPP) schemeLand Cover Type 5: Plant Functional Type (PFT) scheme Additional layers include a Land Cover Type Assessment SDS, a Land Cover Percent SDS, and a Land Cover Quality Control SDS. Collection 5.1 Land Cover Type products are produced with revised training data and certain algorithm refinements. For further details, please consult the following paper: Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., andHuang, X. (2010). MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sensing of Environment, 114, 168-182. Shortname: MCD12Q1 , Platform: Combined Aqua Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 500 m , Temporal Resolution: annual , ArchiveSets: 6 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE41 , File Naming Convention: MCD12Q1.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf AAYYYYDDD = Acquisition Year and Day of Year hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Mark Friedl, Damien Sulla-Menashe - Boston University and MODAPS SIPS - NASA. (2015). MCD12Q1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MCD12Q1.006 , Keywords: Climate Change, Climate Modeling, Land Cover

The Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Dynamics (MCD12Q2) Version 6.1 data product provides global land surface phenology metrics at yearly intervals from 2001 to 2021. The MCD12Q2 Version 6.1 data product is derived from time series of the 2-band Enhanced Vegetation Index (EVI2) calculated from MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR). Vegetation phenology metrics at 500 meter spatial resolution are identified for up to two detected growing cycles per year. For pixels with more than two valid vegetation cycles, the data represent the two cycles with the largest NBAR-EVI2 amplitudes.Provided in each MCD12Q2 Version 6.1 Hierarchical Data Format 4 (HDF4) file are layers for the total number of vegetation cycles detected for the product year, the onset of greenness, greenup midpoint, maturity, peak greenness, senescence, greendown midpoint, dormancy, EVI2 minimum, EVI2 amplitude, integrated EVI2 over a vegetation cycle, as well as overall and phenology metric-specific quality information. SDS layers may be multi-dimensional with up to two valid vegetation cycles. For areas where the NBAR-EVI2 values are missing due to cloud cover or other reasons, the data gaps are filled with good quality NBAR-EVI2 values from the year directly preceding or following the product year.Known Issues Known issues are described in Section 3.2 of the User Guide. * For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.Improvements/Changes from Previous Versions The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). The MCD12Q2 Version 6.1 product has an improved approach to snow filtering.

Estimation of Dominant Land Use / Land Cover per DioceseDATA (details below): 1. MODIS Land Cover, Land Cover Type 2: University of Maryland (UMD) scheme2. Global Diocesan Boundaries, 2.0 2019 (1:3M Scale)DATA PROCESSINGZONAL STATISTICS: MODIS Land Cover, Land Cover Type 2: University of Maryland (UMD) scheme --> Global Diocesan Boundaries, 2.0 2019 (1:3M Scale)NOTE:Values for various landuse and land cover (LULC) codes are in pixels. Pixels were 500m sq. Total represents sum of values between 1 and 17 which represented the actual data. Data pixels with center in a diocese can dived each class by the total to get percentage, more accurately this is not simply the percent of LULC per diocese but a percent of pixels representing LULC in diocese. Values could be used to rank by a particular LULC type or could normalize by area also.Data development:Burhans, Molly A., Cheney, David M., Emege, Thomas, Gerlt, R.. . “Land use and land cover per diocese”. 1:3M. Version 1.0. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.Affiliated Map and Application Development:Molly Burhans, October 2019DATA SET 1: LAND USE LAND COVERGlobal mosaics of the standard MODIS land cover type dataChannan, S., K. Collins, and W. R. Emanuel. 2014. Global mosaics of the standard MODIS land cover type data. University of Maryland and the Pacific Northwest National Laboratory, College Park, Maryland, USA. 2013.ABOUT MODIS LAND COVERINFORMATION QUOTED FROM:URL: https://yceo.yale.edu/modis-land-cover-product-mcd12q1SOURCE: Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., andHuang, X. (2010). MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sensing of Environment, 114, 168–182.

The MCD12Q1 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the MCD12Q1 Version 6.1 data product.

The Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type (MCD12Q1) Version 6 data product provides global land cover types at yearly intervals (2001-2020), derived from six different classification schemes listed in the User Guide. The MCD12Q1 Version 6 data product is derived using supervised classifications of MODIS Terra and Aqua reflectance data. The supervised classifications then undergo additional post-processing that incorporate prior knowledge and ancillary information to further refine specific classes.

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 Hierarchical Data Format 4 (HDF4) file.

Known Issues * The "units" field is missing in the metadata, however, this information can be found in the table above or on page 5 of the User Guide. * Known issues are described on pages 3 and 4 of the User Guide. * For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.

Improvements/Changes from Previous Version * Version 5 used five classification schemes whereas Version 6 uses six classification schemes, including an entirely new classification scheme based on the Land Cover Classification System (LCCS) from the Food and Agricultural Organization (FAO). * New gap-filled spectro-temporal features developed by applying smoothing splines to the Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) time series. This change results in significant changes between land cover classifications in Version 5 and Version 6 data. * Algorithm used in Version 6 includes a post-processing Hidden Markov Model (HMM) that reduces spurious year-to-year variation in class labels. * Algorithm reï¬ nements were implemented in upstream MODIS data used as inputs, such as the cloud mask, surface reflectance, and NBAR data products. * The value of "Water" in the IGBP classification scheme has changed from "0" to "17." * 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. * File size is smaller due to HDF internal compression.

This hybrid 100-m CGLC-MODIS-LCZ global land cover dataset is produced for the Weather Research and Forecasting (WRF) model starting from version 4.5. It is based on 1) the Copernicus Global Land Service Land Cover (CGLC, Buchhorn et al., 2021) product resampled to MODIS IGBP classes (CGLC-MODIS), and 2) the global map of Local Climate Zones (LCZ, Demuzere et al., 2022a, b) that describes the urban and built-up land surface. Both the CGLC and LCZ products are available at a 100-m spatial resolution, are representative for the year 2018, and cover -180°W to 180°E and -60°S to 78°N. Remaining areas are filled with the MODIS land cover classes. This dataset has been implemented into the WRF Preprocessing System (WPS) as tiled binary data files with a new GEOGRID table entry to allow WRF/WPS users to flexibly use this dataset in their studies particularly for urban modeling applications.

To display the dataset in QGIS, cmap_Qgis_CGLC_MOD_LCZ.txt can be used as a color scheme.

For more details, please read the technical documentation: https://doi.org/10.5281/zenodo.7670792.

References:

Buchhorn, M., Smets, B., Bertels, L., De Roo, B., Lesiv, M., Tsendbazar, N.-E., Li, L., Tarko, A. Copernicus Global Land Service: Land Cover 100m: version 3 Globe 2015-2019: Product User Manual (Dataset v3.0, doc issue 3.4). Product User Manual; Zenodo, Geneve, Switzerland, September 2020; doi: 10.5281/zenodo.3938963

Demuzere M, Kittner J, Martilli A, et al. A global map of local climate zones to support earth system modelling and urban-scale environmental science. Earth Syst Sci Data. 2022a;14(8):3835-3873. doi:10.5194/essd-14-3835-2022

Demuzere M, Kittner J, Martilli A, et al. (2022). Global map of Local Climate Zones (2.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6364593

2001 to 2012 OGC WMS global datasets derived from the MODIS Land Cover Type Yearly L3 Global 500 m SIN Grid (MCD12Q1), version 051, Land Cover Type 1 (IGBP) acquired from the NASA Land Processes Distributed Active Archive Center (LP DAAC).

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* Known issues are described on pages 3 and 4 of the User Guide.* For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.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.

Data include a collection of annual land cover maps derived from MODIS 250 m spatial resolution remotely sensed imagery for the period 2000 to 2011. Processing of the time series was designed to reduce the occurrence of false change between maps. The method was based on change updating as described in Pouliot et al. (2011, 2013). Change detection accounted for both abrupt changes such as forest harvesting and more gradual changes such as recurrent insect defoliation. To determine the new label for a pixel identified as change, an evidential reasoning approach was used to combine spectral and contextual information. The 2005 MODIS land cover of Canada at 250 m spatial resolution described in Latifovic et al. (2012) was used as the base map. It contains 39 land cover classes, which for time series development was considered too detailed and was reduced to 25 and 19 class versions. The 19 class version corresponds to the North America Land Change Monitoring System (NALCMS) Level 2 legend as described in Latifovic et al. (2012). Accuracy assessment of time series is difficult due to the need to assess many maps. For areas of change in the time series accuracy was found to be 70% based on the 19 class thematic legend. This time series captures the spatial distribution of dominant land cover transitions. It is intended for use in modeling, development of remote sensing products such as leaf area index or land cover based albedo retrievals, and other exploratory analysis. It is not appropriate for use in any rigorous reporting or inventory assessments due to the accuracy of the land cover classification and uncertainty as to the capture of all relevant changes for an application. NOTE: To see this entire product in the map viewer, use a base map in the "World" section (EPSG: 3857).

The Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) (MCD12C1) Version 6.1 data product provides a spatially aggregated and reprojected version of the tiled MCD12Q1 Version 6.1 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 2022. 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 6.1 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 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.Improvements/Changes from Previous Versions The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).* The MCD12C1 Version 6.1 product has a minor fix to UMD Land Cover Class.

FireMAFS was led by Prof Martin Wooster (Kings College, London) as part of QUEST Theme 3 (Quantifying and Understanding the Earth System) project. The objective of FireMAFS was to resolve limitations of fire modelling by developing a robust method to forecast fire activity (fire 'danger' indices, ignition probabilities, burnt area, fire intensity etc), via a process-based model of fire-vegetation interactions, tested, improved, and constrained. This used a state-of-the-art EO data products and driven by seasonal weather forecasts issued with many months lead-time. This dataset contains the MODIS Land Cover Type product multiple classification schemes, which describe land cover properties derived from observations spanning a year’s input of Terra and Aqua data. The data are stored in a 10 arc minute grid.

China's land cover data set includes 5 products: 1) glc2000_lucc_1km_China.asc, a Chinese subset of global land cover data based on SPOT4 remote sensing data developed by the GLC2000 project. The data name is GLC2000.GLC2000 China's regional land cover data is directly cropped from global cover data. For data description, please refer to http : //www-gvm.jrc.it/glc2000/defaultGLC2000.htm 2) igbp_lucc_1km_China.asc, a Chinese subset of global land cover data based on AVHRR remote sensing data supported by IGBP-DIS, the data name is IGBPDIS; IGBPDIS data was prepared using the USGS method, using April 1992 to March 1992 The AVHRR data developed global land cover data with a resolution of 1km. The classification system adopts a classification system developed by IGBP, which divides the world into 17 categories. Its development is based on continents. Applying AVHRR for 12 months to maximize synthetic NDVI data, 3) modis_lucc_1km_China_2001.asc, a subset of MODIS land cover data products in China, the data name is MODIS; MODIS China's regional land cover data is directly cropped from global cover data, and its data description please refer to http://edcdaac.usgs.gov/ modis / mod12q1v4.asp. 4. umd_lucc_1km_China.asc, a Chinese subset of global land cover data based on AVHRR data produced by the University of Maryland, the data name is UMd; the five bands of UMd based on AVHRR data and NDVI data are recombined to suggest a data matrix, using Methodology carried out global land cover classification. The goal is to create data that is more accurate than past data. The classification system largely adopts the classification scheme of IGBP. 5) westdc_lucc_1km_China.asc, China ’s 2000: 100,000 land cover data organized and implemented by the Chinese Academy of Sciences, combined with Yazashi conversion (the largest area method), and finally obtained a land use data product of 1km across the country, data name WESTDC. WESTDC China's regional land cover data is based on the results of a 1: 100,000 county-level land resource survey conducted by the Chinese Academy of Sciences. The land use data were merged and converted into a vector (the largest area method). The Chinese Academy of Sciences resource and environment classification system is adopted. 2: Data format: ArcView GIS ASCII 3: Mesh parameters: ncols 4857 nrows 4045 xllcorner -2650000 yllcorner 1876946 cellsize 1000 NODATA_value -9999 4: Projection parameters: Projection ALBERS Units METERS Spheroid Krasovsky Parameters: 25 00 0.000 / * 1st standard parallel 47 00 0.000 / * 2nd standard parallel 105 00 0.000 / * central meridian 0 0 0.000 / * latitude of projection's origin 0.00000 / * false easting (meters) 0.00000 / * false northing (meters)

Data include a collection of annual land cover maps derived from MODIS 250 m spatial resolution remotely sensed imagery for the period 2000 to 2011. Processing of the time series was designed to reduce the occurrence of false change between maps. The method was based on change updating as described in Pouliot et al. (2011, 2013). Change detection accounted for both abrupt changes such as forest harvesting and more gradual changes such as recurrent insect defoliation. To determine the new label for a pixel identified as change, an evidential reasoning approach was used to combine spectral and contextual information. The 2005 MODIS land cover of Canada at 250 m spatial resolution described in Latifovic et al. (2012) was used as the base map. It contains 39 land cover classes, which for time series development was considered too detailed and was reduced to 25 and 19 class versions. The 19 class version corresponds to the North America Land Change Monitoring System (NALCMS) Level 2 legend as described in Latifovic et al. (2012). Accuracy assessment of time series is difficult due to the need to assess many maps. For areas of change in the time series accuracy was found to be 70% based on the 19 class thematic legend. This time series captures the spatial distribution of dominant land cover transitions. It is intended for use in modeling, development of remote sensing products such as leaf area index or land cover based albedo retrievals, and other exploratory analysis. It is not appropriate for use in any rigorous reporting or inventory assessments due to the accuracy of the land cover classification and uncertainty as to the capture of all relevant changes for an application.

These data provide land cover classifications derived from the Boston University MOD12Q1 V004 MODIS/Terra 1 km Land Cover Product (Friedl et al. 2002). The data are available in various EASE-Grid azimuthal and global projections, in 12.5 km and 25 km spatial resolutions. The data are in flat binary, 1 byte files that are stored by row.

These data provide land cover classifications derived from the Boston University MOD12Q1 V004 MODIS/Terra 1 km Land Cover Product (Friedl et al. 2002). The data are available in various EASE-Grid 2.0 azimuthal and global projections, in multiple spatial resolutions ranging from 3 km to 100 km.The data are in flat binary, 1 byte files that are stored by row.

Data set development attribution: Channan, S., K. Collins, and W. R. Emanuel. 2014. Global mosaics of the standard MODIS land cover type data. University of Maryland and the Pacific Northwest National Laboratory, College Park, Maryland, USA. MODIS standard data product attribution: Friedl, M.A., D. Sulla-Menashe, B. Tan, A. Schneider, N. Ramankutty, A. Sibley and X. Huang (2010), MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets, 2001-2012, Collection 5.1 IGBP Land Cover, Boston University, Boston, MA, USA. Dataset found at: http://glcf.umd.edu/data/lc/

ABSTRACT: The objective of the MODIS Land Cover Product is to provide a suite of land cover types useful to global system science modelers by exploiting the information content of MODIS data in the spectral, temporal, spatial, and directional domains. These are global land cover classifications (dominant type, classification confidence and fractional cover) generated using a full year of MODerate Resolution Imaging Spectroradiometer (MODIS) data covering the period from October 2000 to October 2001. These products describe the geographic distribution of the 17 land cover classification scheme proposed by the International Geosphere-Biosphere Programme (IGBP).

This data set, ISLSCP II MODIS (Collection 4) IGBP Land Cover, 2000-2001, contains global land cover classifications (dominant type, classification confidence and fractional cover) generated using a full year of MODerate Resolution Imaging Spectroradiometer (MODIS) data covering the period from October 2000 to October 2001. The objective of the MODIS Land Cover Product is to provide a suite of land cover types useful to global system science modelers by exploiting the information content of MODIS data in the spectral, temporal, spatial, and directional domains. These products describe the geographic distribution of the 17 land cover classification scheme proposed by the International Geosphere-Biosphere Programme (IGBP).