N: 90 S: -90 E: 180 W: -180
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.
- 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.
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 (A2024001), the Tile Identifier which is horizontal tile and vertical tile provided as hXXvYY (h21v07), the Version of the data collection (061), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2025205222320), and the Data Format (hdf).
Documents
USER'S GUIDE
ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)
PRODUCT QUALITY ASSESSMENT
SCIENCE DATA PRODUCT VALIDATION
Dataset Resources
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| A dataset on metal-related production activities and their socio-environmental impacts in Canada | Pellan, Marin, Greffe, Titouan, Majeau-Bettez, Guillaume, de Bortoli, Anne | Land Use/Land Cover Classification | |
| A deep learning method for generating gap-free FAPAR time series from | Zhang, Guodong, Yin, Gaofei, Zhao, Wei, Wang, Meilian, Verger, Aleixandre | Land Use/Land Cover Classification | |
| A global land-use data cube 19922020 based on the Human Appropriation of Net Primary Production | Matej, Sarah, Weidinger, Florian, Kaufmann, Lisa, Roux, Nicolas, Gingrich, Simone, Haberl, Helmut, Krausmann, Fridolin, Erb, Karl-Heinz | Land Use/Land Cover Classification | |
| An enhanced phenology dataset for global drylands from 2001 to 2019 | Dong, Yuqi, Zhou, Yu, Zhang, Li, Tian, Feng, Xie, Qiaoyun, Chen, Yiyang, Ruan, Linlin, Zhang, Bo | Land Use/Land Cover Classification, Reflectance, Anisotropy, Plant Phenology, Enhanced Vegetation Index (EVI), Vegetation Index, Plant Phenological Changes, Plant Characteristics, Vegetation Cover | |
| An annual cropland extent dataset for Africa at 30 m spatial resolution from 2000 to 2022 | Lou, Zihang, Peng, Dailiang, Shi, Zhou, Wang, Hongyan, Liu, Ke, Zhang, Yaqiong, Yan, Xue, Chen, Zhongxing, Ye, Su, Yu, Le, Hu, Jinkang, Lv, Yulong, Peng, Hao, Zhang, Yizhou, Zhang, Bing | Crop/Plant Yields, Landscape Patterns, Cropland, Land Use/Land Cover Classification | |
| Analyzing wildfire patterns and climate interactions in Campania, Italy: | Dadkhah, Hanieh, Rana, Divyeshkumar, Ghaderpour, Ebrahim, Mazzanti, Paolo | Land Use/Land Cover Classification | |
| Assessing the SMAP Level-4 Carbon Product over the Arctic and Subarctic Zones | Madelon, Remi, Kimball, John S., Endsley, K. Arthur, De Lannoy, Gabrielle J. M., Sonnentag, Oliver, Alcock, Haley, Detto, Matteo, Virkkala, Anna M., Rogers, Brendan M., Watts, Jennifer D., Mavrovic, Alex, Williamson, Scott N., Humphreys, Elyn, Colliander, Andreas, Mialon, Arnaud, Roy, Alexandre | Land Use/Land Cover Classification, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar) | |
| Assessing the utility of machine learning for predicting food sufficiency: a case study in Malawi | Tomes, Andrew, Gholami, Shahrzad, Alia, Didier, Hennessy, Conor, Xu, Dafeng, Bitz, Cecilia, Dodhia, Rahul, Lavista Ferres, Juan, Anderson, C. Leigh | Land Use/Land Cover Classification, Land Surface Temperature, Emissivity | |
| Assessing the Impact of Multi-Decadal Land Use Change on Agricultural | Gemechu, Tewekel Melese, Zhang, Huifang, Sun, Jialong, Chen, Baozhang | Land Use/Land Cover Classification | |
| Assessing the Interaction Between Agricultural, Hydrological, and Meteorological Droughts in the Tigris River Basin | Valizadeh Kamran, Khalil, Dhiab, Ayat, Abdulkareem, Hala | Land Use/Land Cover Classification, Albedo, Anisotropy | |
| Assessment of global land cover changes using satellite data: | Chen, Shuo, Zhuang, Qianlai, Taheripour, Farzad, Yuan, Ye, Benavidez, Lauren | Land Use/Land Cover Classification | |
| Assessment of vegetation restoration potential in central Asia | Lv, Zhentao, Li, Shengyu, Xu, Xinwen, Lei, Jiaqiang, Peng, Zhongmin | Land Use/Land Cover Classification | |
| Assessing the Effects of Climate Change and Anthropogenic Contributions in Parishan Wetland, Iran | Kazemi Garajeh, Mohammad, Valizadeh Kamran, Khalil, Feizizadeh, Bakhtiar, Ghaffari Aliabad, Omid, Saei, Mousa, Sadeqi, Amin | Land Use/Land Cover Classification, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Assessing the elevational synchronization in vegetation phenology across | Yang, Chen, Tian, Feng, Jin, Hongxiao, Fensholt, Rasmus, Feng, Luwei, Tagesson, Torbern | Land Use/Land Cover Classification | |
| Assessing the impact of extreme climate events on European gross primary | Zhang, Huihui, Loaiciga, Hugo A, Okujeni, Akpona, Liu, Ji, Tan, Min, Sauter, Tobias | Land Use/Land Cover Classification, Photosynthesis, Primary Production, Vegetation Productivity, Evapotranspiration, Latent Heat Flux | |
| Applications of Machine Learning and Artificial Intelligence in | Hickman, Sebastian H. M., Kelp, Makoto M., Griffiths, Paul T., Doerksen, Kelsey, Miyazaki, Kazuyuki, Pennington, Elyse A., Koren, Gerbrand, Iglesias-Suarez, Fernando, Schultz, Martin G., Chang, Kai-Lan, Cooper, Owen R., Archibald, Alex, Sommariva, Roberto, Carlson, David, Wang, Hantao, West, J. Jason, Liu, Zhenze | Population Size, Land Use/Land Cover Classification | |
| Artificial light at night outweighs temperature in lengthening urban growing seasons | Wang, Lvlv, Meng, Lin, Richardson, Andrew D., Holker, Franz, Li, Huidong, Mao, Jiafu, Longcore, Travis, Xia, Jun, She, Dunxian | Land Use/Land Cover Classification | |
| Analyses of MODIS land cover/use and wildfires in Italian regions since 2001 | Ghaderpour, Ebrahim, Bozzano, Francesca, Scarascia Mugnozza, Gabriele, Mazzanti, Paolo | Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow, Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Emissivity, Land Surface Temperature | |
| Analysis of Net Primary Productivity Trends in India by Incorporating the Direct Effect of CO2 Fertilization in MODIS Data | Das, Ripan, Karmakar, Subhankar, Ghosh, Subimal | Land Use/Land Cover Classification, Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Leaf Area Index (LAI), Photosynthesis, Primary Production, Vegetation Productivity, Atmospheric Radiation, Longwave Radiation, Shortwave Radiation, Radiative Flux, Radiative Forcing, Surface Radiative Properties, Albedo, Emissivity, Cloud Properties, Cloud Fraction, Cloud Optical Depth/Thickness, Skin Temperature, Skin Temperature, Sea Surface Skin Temperature, Terrain Elevation, Digital Elevation/Terrain Model (DEM), Topographical Relief Maps, Geopotential Height, Altitude, Surface Temperature, Upper Air Temperature, Dew Point Temperature, Air Temperature, Cloud Top Temperature, Atmospheric Winds, Surface Winds, U/V Wind Components, Upper Level Winds, U/V Wind Components, Vertical Wind Velocity/Speed, Atmospheric Pressure, Sea Level Pressure, Cloud Top Pressure, Sea Level Pressure, Surface Pressure, Specific Humidity, Total Precipitable Water, Cloud Liquid Water/Ice, Atmospheric Water Vapor, Atmospheric Ozone, Oxygen Compounds, Boundary Layer Winds, Total Ozone | |
| Anthropogenic and climatic drivers of the 2022 mega-flood in Pakistan | Arshad, Arfan, Mirchi, Ali, He, Cenlin, Shah, Azeem Ali, AghaKouchak, Amir | Land Use/Land Cover Classification | |
| Applicability of a Sine-Random Forest Hybrid Method for meteorological | Zhang, Siyao, Li, Jianzhu, Zhang, Ting, Tian, Jiyang, Feng, Ping | Heat Flux, Air Temperature, Skin Temperature, Specific Humidity, Water Vapor, Precipitation Rate, Snow/Ice, Evaporation, Latent Heat Flux, Latent Heat Flux, Sensible Heat Flux, Diffusion, Surface Winds, Wind Speed, U/V Wind Components, Wind Stress, Wind Stress, Surface Roughness, Planetary Boundary Layer Height, Ice Fraction, Longwave Radiation, Shortwave Radiation, Soil Heat Budget, Soil Heat Budget, Soil Temperature, Soil Temperature, Soil Infiltration, Soil Infiltration, Soil Moisture/Water Content, Surface Soil Moisture, Root Zone Soil Moisture, Soil Moisture/Water Content, Surface Water, Runoff Rate, Average Flow, Average Flow, Precipitation, Snow Depth, Snow Melt, Snow/Ice Temperature, Leaf Area Index (LAI), Leaf Area Index (LAI), Surface Pressure, Surface Temperature, Humidity, Evapotranspiration, Surface Winds, Rain, Snow, Land Surface Temperature, Snow Water Equivalent, Runoff, Land Use/Land Cover Classification | |
| An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product | Chen, Siyuan, Liu, Liangyun, Sui, Lichun, Liu, Xinjie, Ma, Yan | Land Use/Land Cover Classification, Albedo, Anisotropy, Reflectance | |
| Association Between Deforestation and the Incidence of Snakebites in South Korea | Lee, Seoheui, Lee, Junyeong, Min, Kyung-Duk | Land Use/Land Cover Classification | |
| Asymmetric spatial anomaly patterns of precipitation between light and very heavy precipitation over Indian urban agglomerations | Kalamalla, Lokesh, Satyanarayana, A. N. V. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Land Use/Land Cover Classification | |
| AutoMergeNet: AutoML-Based M-Source Satellite Data Fusion Evaluated With | Wasala, Julia, Maasakkers, Joannes D., Schuit, Berend J., Leguijt, Gijs, Aben, Ilse, Schneider, Rochelle, Hoos, Holger, Baratchi, Mitra | Land Use/Land Cover Classification |