N: 90 S: -90 E: 180 W: -180
Description
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.
Version Description
Product Summary
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
File Naming Convention
The file name begins with the Product Short Name (MCD12Q1) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2003001), the Tile Identifier which is horizontal tile and vertical tile provided as hXXvYY (h16v00), the Version of the data collection (006), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2018144112435), and the Data Format (hdf).
Documents
USER'S GUIDE
ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)
PRODUCT QUALITY ASSESSMENT
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| A hybrid machine learning model for flood prediction with recursive feature elimination informed by training performance | Gong, Liying, Woo, Wai Lok, Wu, Yue Ivan, Zheng, Xiujuan | RADAR IMAGERY, Terrain Elevation, Topographical Relief Maps, Digital Elevation/Terrain Model (DEM), Land Use/Land Cover Classification, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| A high performance assimilation of surface soil moisture based on a | Zhu, Shuang, Zha, Gang, Wang, Qi, Ma, Siyu, Qin, Hui | Land Use/Land Cover Classification | |
| A localized plant species-specific BVOC emission rate library of China established using a developed statistical approach based on field measurements | Han, Huijuan, Jia, Yanqi, Shi, Rende, Nie, Changliang, Kajii, Yoshizumi, Wu, Yan, Li, Lingyu | Land Use/Land Cover Classification | |
| Advancing ecohydrological modelling: coupling LPJ-GUESS with ParFlow for integrated vegetation and surface-subsurface hydrology simulations | Jia, Zitong, Chen, Shouzhi, Fu, Yongshuo H., Martin Belda, David, Warlind, David, Olin, Stefan, Xu, Chongyu, Tang, Jing | Plant Phenology, Enhanced Vegetation Index (EVI), Land Use/Land Cover Classification | |
| Advancing point-to-grid scale ET mapping: comparative assessment of ECOSTRESS and MODIS LST and ET across heterogeneous landscapes | Park, Kijin, Baik, Jongjin, Kim, Kiyoung, Park, Jongmin | Evapotranspiration, Latent Heat Flux, Geolocation, Land Use/Land Cover Classification, Land Surface Temperature, Emissivity, Clouds | |
| Active Fire Dynamics in Venezuela | Correia Filho, Washington Luiz Felix, Freire, Felipe Machado, de Oliveira-Junior, Jose Francisco, Santiago, Dimas de Barros, Paredes-Trejo, Franklin, Pereira, Carlos Rodrigues, Abdo, Hazem Ghassan | Land Use/Land Cover Classification, Land Surface Temperature, Emissivity, Evapotranspiration, Latent Heat Flux, Photosynthesis, Primary Production | |
| All-sky hourly estimation over East Asia using Himawari-8 AHI and | Bae, Sejeong, Son, Bokyung, Sung, Taejun, Kim, Yejin, Kim, Youngseok, Im, Jungho | Land Use/Land Cover Classification | |
| Alpha, beta and gamma diversity in relatively natural, mixed and transformed landscape scenarios | Deng, Shuyu, Beale, Colin M., Thomas, Chris D. | Land Use/Land Cover Classification | |
| A super-resolution framework for downscaling machine learning weather prediction toward 1-km air temperature | Park, Hyebin, Park, Seonyoung, Kang, Daehyun, Kim, Jeong-Hwan | Land Use/Land Cover Classification, Land Surface Temperature, Emissivity | |
| Assessing the Impacts of Long-Term Weather Variability and Urban Development on Crop Production to Analyze Food Security in Iran | Garajeh, Mohammad Kazemi, Kamran, Khalil Valizadeh, Feizizadeh, Bakhtiar, Khorrami, Behnam | Land Use/Land Cover Classification, Evapotranspiration, Photosynthesis, Primary Production, Latent Heat Flux, Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow | |
| Warmer climate disrupts the trade-off between post-fire loss and recovery of grassland GPP | Cui, Guishan, Ding, Yitong, Xu, Zhen | Land Use/Land Cover Classification, Fire Ecology, Biomass Burning, Wildfires, Fire Occurrence, Burned Area | |
| Water scarcity indicator based on GRACE derived total water storage for fast water scarcity monitoring | Wolkeba, Fitsume T., Mekonnen, Mesfin M., Brauman, Kate A. | Land Use/Land Cover Classification | |
| Waterfowl Move Less in Heterogeneous and Human-Populated Landscapes | Teitelbaum, Claire S., Prosser, Diann J., Ackerman, Joshua T., Ahmed, Sakib, Alam, A. B. M. Sarowar, Azmiri, Kazi Zenifar, Batbayar, Nyambaya, Bety, Joel, BlakeBradshaw, Abigail, Boiko, Dmitrijs, Buitendijk, Nelleke H., Buler, Jeffrey J., Cabot, David, Casazza, Michael L., Cohen, Bradley, Davaasuren, Batmunkh, Farau, Sebastien, Feddersen, Jamie, Fieberg, John, Fiedler, Wolfgang, Glazov, Peter, Griffin, Larry R., Guillemain, Matthieu, Hagy, Heath, Hardy, Matthew J., Highway, Cory, Hoffman, David, Kang, Tehan, Keever, Allison, Kilburn, Jennifer, Kolzsch, Andrea, Kruckenberg, Helmut, Laaksonen, Toni, Ladman, Brian S., Lee, Hansoo, Lee, Siwan, Lefebvre, Josee, Legagneux, Pierre, Linssen, Hans, Madsen, Jesper, Masto, Nicholas M., McWilliams, Scott, Mezebish Quinn, Tori, Mitchell, Carl, Moreau, Axelle, Muskens, Gerhard, Newman, Scott, Nolet, Bart A., Nuijten, Rascha J. M., Osenkowski, Jay, Overton, Cory T., Piironen, Antti, Plaquin, Betty, Ramey, Andrew M., Rodrigue, Jean, Rodrigues, David, Schreven, Kees H. T., Si, Yali, Sullivan, Jeffery D., Takekawa, John, Thomas, Philippe J., van Toor, Marielle, Waldenstrom, Jonas, Williams, Christopher K., Wolfson, David W., Xu, Fei, Brosnan, Ian G., De La Cruz, Susan E. W. | Plant Phenology, Enhanced Vegetation Index (EVI), Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI) | |
| Weakening mountain vegetation aspect asymmetry due to altered energy conditions | Tian, Qing, Tian, Feng | Plant Phenology, Enhanced Vegetation Index (EVI), Land Use/Land Cover Classification, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar) | |
| Vegetation cover dynamics of the Dniester basin under climate change influence in the 21st century. | Salyha, Volodymyr, Arkhypova, Liudmyla | Land Use/Land Cover Classification, Land Surface Temperature, Emissivity | |
| Lagged effect of temperature and rainfall on malaria incidence in Colombia (20132023): An approach with Bayesian spatiotemporal adjustment | Gutierrez, Juan David | Land Use/Land Cover Classification | |
| Integrating Satellite and Climate Data for Crop Yield Prediction: Spatiotemporal Analysis and Neural Network based Model | Zena H. Khalil | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Land Use/Land Cover Classification | |
| Integrating causal inference and machine learning to quantify climate-malaria relationships: Evidence of temperature and rainfall thresholds from Colombian municipalities | Gutierrez, Juan David | Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | |
| Heat requirement, not warming, governs the urbanrural disparity in spring phenology advancement | He, Can, Wang, Xiaoyue, Penuelas, Josep, Zhang, Xuezhen, Wu, Chaoyang | Plant Phenology, Enhanced Vegetation Index (EVI), Land Use/Land Cover Classification, Reflectance, Albedo, Anisotropy, Shortwave Radiation | |
| Impact of land-use change on ecosystem services in Africa's Great Green | Wang, Yizhuo, Scott, Catherine E., Dallimer, Martin | Land Use/Land Cover Classification, Plant Phenology, Enhanced Vegetation Index (EVI), Vegetation Index, Normalized Difference Vegetation Index (NDVI), Evapotranspiration, Latent Heat Flux, Topographical Relief Maps, Terrain Elevation, Digital Elevation/Terrain Model (DEM) | |
| From Descriptors to Decisions: Structuring the Libyan National Land Cover Reference System with Land Cover Meta Language | Nwer, Bashir, Dadhich, Gautam, Alkasih, Akram, Maki, Abdourahman, Mushtaq, Fatima | Land Use/Land Cover Classification | |
| Geospatially-Aware Multi-Modal Fusion for Satellite Image Manipulation Detection | Chapman, Matthew W, Tewkesbury, Andrew, Boyd, Doreen S, Obara, Boguslaw, Bhowmik, Deepayan | Land Use/Land Cover Classification | |
| Hybrid MCDMIsolation Forest approach for spatiotemporal landslide mapping | Jiang, Bingqi, Wang, Shouwu, Han, Chunhua, Meng, Jingkai, Wang, Lida | Terrain Elevation, RADAR IMAGERY, Topographical Relief Maps, Land Use/Land Cover Classification | |
| Geological regulation of nitrous oxide emission risks in rivers globally | Qi, Hongkai, Liu, Yi, Wang, Haoran, Pang, Yu, Li, Junyu, Ma, Xiao, Wu, Longjun, He, Ding, Gan, Jianping | Land Use/Land Cover Classification | |
| Improving GLASS AVHRR-derived terrestrial shortwave blue-sky albedo using GLASS MODIS-derived albedo: a global long-term study | Yang, Zi, Zhu, Hongjun, Yuan, Jie, Guluzade, Rufat, Pan, Xin, Ding, Xu, Liu, Suyi, Zhu, Congbao, Li, Yuqian, Guo, Longlong, Yang, Yingbao | Land Use/Land Cover Classification |
Variables
The table below lists the variables contained within a single granule for this dataset. Variables often contain observed or derived geophysical measurements collected from a variety of sources, including remote sensing instruments on satellite and airborne platforms, field campaigns, in situ measurements, and model outputs. The terms variable, parameter, scientific data set, layer, and band have been used across NASA’s Earth science disciplines; however, variable is the designated nomenclature in NASA’s Common Metadata Repository (CMR). Variable metadata attributes such as Name, Description, Units, Data Type, Fill Value, Valid Range, and Scale Factor allow users to efficiently process and analyze the data. The full range of attributes may not be applicable to all variables. Additional information on variable attributes is typically available in the data, user guide, and/or other product documentation.
For questions on a specific variable, please use the Earthdata Forum.
| Name Sort descending | Description | Units | Data Type | Fill Value | Valid Range | Scale Factor | Offset |
|---|---|---|---|---|---|---|---|
| LC_Prop1 | FAO-Land Cover Classification System 1 (LCCS1) land cover layer | Class | uint8 | 255 | 1 to 43 | N/A | N/A |
| LC_Prop1_Assessment | LCCS1 land cover layer confidence | Percent | uint8 | 255 | 0 to 100 | N/A | N/A |
| LC_Prop2 | FAO-LCCS2 land use layer | Class | uint8 | 255 | 1 to 40 | N/A | N/A |
| LC_Prop2_Assessment | LCCS2 land use layer confidence | Percent | uint8 | 255 | 0 to 100 | N/A | N/A |
| LC_Prop3 | FAO-LCCS3 surface hydrology layer | Class | uint8 | 255 | 1 to 51 | N/A | N/A |
| LC_Prop3_Assessment | LCCS3 surface hydrology layer confidence | Percent | uint8 | 255 | 0 to 100 | N/A | N/A |
| LC_Type1 | Land Cover Type 1: Annual International Geosphere-Biosphere Programme (IGBP) classification | Class | uint8 | 255 | 1 to 17 | N/A | N/A |
| LC_Type2 | Land Cover Type 2: Annual University of Maryland (UMD) classification | Class | uint8 | 255 | 0 to 15 | N/A | N/A |
| LC_Type3 | Land Cover Type 3: Annual Leaf Area Index (LAI) classification | Class | uint8 | 255 | 0 to 10 | N/A | N/A |
| LC_Type4 | Land Cover Type 4: Annual BIOME-Biogeochemical Cycles (BGC) classification | Class | uint8 | 255 | 0 to 8 | N/A | N/A |
| LC_Type5 | Land Cover Type 5: Annual Plant Functional Types classification | Class | uint8 | 255 | 0 to 11 | N/A | N/A |
| LW | Binary land (class 2) / water (class 1) mask derived from MOD44W | Class | uint8 | 255 | 1 to 2 | N/A | N/A |
| QC | Product quality flags | Quality Flag | uint8 | 255 | 0 to 10 | N/A | N/A |