N: 90 S: -90 E: 180 W: -180
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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
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Machine learning and global vegetation: random forests for downscaling and gap filling | van Jaarsveld, Barry, Hauswirth, Sandra M., Wanders, Niko | Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | |
| Mapping specific groundwater nitrate concentrations from spatial data using machine learning: A case study of chongqing, China | Liang, Yuanyi, Zhang, Xingjun, Gan, Lin, Chen, Si, Zhao, Shandao, Ding, Jihui, Kang, Wulue, Yang, Han | Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | |
| Long-Term Satellite Monitoring of Various Types of Wildfires and Wildfire-Induced Emissions of Climate-Active Gases and Aerosols in Russia and in Its Large Regions | Bondur, V. G., Zima, A. L., Feoktistova, N. V. | Land Use/Land Cover Classification, Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES, Fire Ecology, Biomass Burning, Wildfires, Burned Area | |
| Long-term trends of vegetation greenness under different urban | Zhong, Qikang, Li, Zhe | Land Use/Land Cover Classification | |
| Loss and recovery of vegetation productivity in response to extreme | Li, Meng, Cui, Rui, Bu, Lingjia, Yang, Yuting | Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | |
| Numerical Weather Forecast and Multi-Meteorological Data Fusion Based on Artificial Intelligence | Yang, Yuanjian, Wang, Shuai, Zheng, Wenjian, Zhou, Shaohui, Duan, Zexia, Wang, Mengya | Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Photosynthesis, Primary Production, Vegetation Productivity | |
| Optimizing malaria vector control in the Greater Mekong Subregion: a systematic review and mathematical modelling study to identify desirable intervention ... | Wang, Yuqian, Chitnis, Nakul, Fairbanks, Emma L. | Land Use/Land Cover Classification | |
| On the importance of plant phenology in the evaporative process of a semi-arid woodland: could it be why satellite-based evaporation estimates in the ... | Zimba, Henry M., Coenders-Gerrits, Miriam, Banda, Kawawa E., Hulsman, Petra, van de Giesen, Nick, Nyambe, Imasiku A., Savenije, Hubert H. G. | Photosynthetically Active Radiation, Leaf Area Index (LAI), Leaf Characteristics, Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Reflectance, Land Use/Land Cover Classification, Evapotranspiration, Latent Heat Flux, Terrain Elevation, Digital Elevation/Terrain Model (DEM), Topographical Relief Maps | |
| A Synoptic-Scale Comparison of Satellite Yukon River Mouth Temperature to In-Situ and Reanalysis Data During 20032020 | Spratt, Rachel, Vazquez, Jorge, Carroll, Dustin | 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, Skin Temperature, Land Use/Land Cover Classification, Wind Speed | |
| Adverse Effects of Ozone Pollution on Net Primary Productivity in the | Long, X., Han, Y., Wang, Q. Y., Li, X. K., Feng, T., Wang, Y. C., Wang, Y., Zhang, S. L., Han, Y. M., Li, G. H., Tie, X. X., Cao, J. J., Chen, Y. | Land Use/Land Cover Classification, Photosynthesis, Primary Production, Vegetation Productivity | |
| Accurate and Efficient Numerical Simulation of Land Models Using SUMMA | Spiteri, Raymond J., Van Beusekom, Ashley E., Klenk, Kyle, Zolfaghari, Reza, Trim, Sean J., Knoben, Wouter J. M., Ireson, Andrew M., Clark, Martyn P. | Land Use/Land Cover Classification | |
| An Unstructured Mesh Generation Tool for Efficient High-Resolution | Fan, Hanwen, Xu, Qingchen, Bai, Fan, Wei, Zhongwang, Zhang, Yonggen, Lu, Xingjie, Wei, Nan, Zhang, Shupeng, Yuan, Hua, Liu, Shaofeng, Li, XianXiang, Li, Xueyan, Dai, Yongjiu | Land Use/Land Cover Classification | |
| An Insight Into the Internal Consistency of MODIS Global Leaf Area Index | Zhang, Xingjian, Yan, Kai, Liu, Jinxiu, Yang, Kai, Pu, Jiabin, Yan, Guangjian, Heiskanen, Janne, Zhu, Peng, Knyazikhin, Yuri, Myneni, Ranga B. | Land Use/Land Cover Classification | |
| An integrated framework for jointly assessing spatiotemporal dynamics of | Wang, Yuan, Wang, Han, Yao, Fei, Stouffs, Rudi, Wu, Jiansheng | Land Use/Land Cover Classification | |
| An investigation on potential dispersal of airborne pollen over China and their impact on climate as ice nuclei using RegCMpollen | Song, Rong, Wang, Tijian, Li, Shu, Zhuang, Bingliang, Li, Mengmeng, Xie, Min, Luo, Chuanxiu, KilifarskaNedialkova, Natalya Andreeva | Land Use/Land Cover Classification | |
| A global assessment of the effects of solar farms on albedo, vegetation, and land surface temperature using remote sensing | Xu, Zhengjie, Li, Yan, Qin, Yingzuo, Bach, Eviatar | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Land Surface Temperature, Emissivity, Land Use/Land Cover Classification, Albedo, Anisotropy | |
| A Sequence-to-Sequence Transformer Model for Satellite Retrieval of | Zhang, Luo, Gu, Haoran, Li, Zhengqiang, Liu, Zhenhai, Zhang, Ying, Xie, Yisong, Zhang, Zihan, Ji, Zhe, Li, Zhiyu, Yan, Chaoyu | Land Use/Land Cover Classification | |
| A systematic review of urban heat island and heat waves research (1991 - | Cheval, Sorin, Amihaesei, Vlad-Alexandru, Chitu, Zenaida, Dumitrescu, Alexandru, Falcescu, Vladut, Irasoc, Adrian, Micu, Dana Magdalena, Mihulet, Eugen, Ontel, Irina, Paraschiv, Monica-Gabriela, Tudose, Nicu Constantin | Land Use/Land Cover Classification | |
| A New Machine-Learning-Based Calibration Scheme for MODIS Thermal | Xu, Jiafei, Liu, Zhizhao, Hong, Guan, Cao, Yunchang | Land Use/Land Cover Classification | |
| A new assessment framework to forecast land use and carbon storage under different SSP-RCP scenarios in China | Guo, Wei, Teng, Yongjia, Li, Jing, Yan, Yueguan, Zhao, Chuanwu, Li, Yongxing, Li, Xiang | Land Use/Land Cover Classification | |
| A new framework for evaluating dust emission model development using dichotomous satellite observations of dust emission | Hennen, Mark, Chappell, Adrian, Webb, Nicholas P., Schepanski, Kerstin, Baddock, Matthew C., Eckardt, Frank D., Kandakji, Tarek, Lee, Jeffrey A., Nobakht, Mohamad, von Holdt, Johanna | Land Use/Land Cover Classification, Reflectance, Albedo, Anisotropy | |
| A Multisource Data Approach for Change and Disturbance Mapping of Ontario's Clay Belt Towards More Accurate Carbon and Emissions Estimation | Ituen, Ima, Hu, Baoxin | Land Use/Land Cover Classification, Fire Ecology, Biomass Burning, Wildfires, Fire Occurrence, Burned Area | |
| A performance evaluation of random forest, artificial neural network, and support vector machine learning algorithms to predict spatio-temporal land use-land cover ... | Mutale, Bwalya, Withanage, Neel Chaminda, Mishra, Prabuddh Kumar, Shen, Jingwei, Abdelrahman, Kamal, Fnais, Mohammed S. | Land Use/Land Cover Classification | |
| A novel AMSR2 retrieval algorithm for global C-band vegetation optical depth and soil moisture (AMSR2 IB): Parameters' calibration, evaluation and inter-comparison | Wang, Mengjia, Ciais, Philippe, Frappart, Frederic, Tao, Shengli, Fan, Lei, Sun, Rui, Li, Xiaojun, Liu, Xiangzhuo, Wang, Huan, Wigneron, Jean-Pierre | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Temperature, Soil Moisture/Water Content, Land Use/Land Cover Classification, Photosynthetically Active Radiation, Leaf Area Index (LAI), Leaf Characteristics, Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Vegetation Water Content, Skin Temperature | |
| A novel approach for retrieving GPP of evergreen forest regions of India using random forest regression | Sarkar, Deep Prakash, Uma Shankar, B., Ranjan Parida, Bikash | Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) |