N: 90 S: -90 E: 180 W: -180
Description
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.
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 (MCD12C1) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2003001), the Version of the data collection (006), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2018053185458), and the Data Format (hdf).
Documents
USER'S GUIDE
ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Constraining orientation statistics of ice crystals in clouds with observations from deep space | Kostinski, Alexander, Marshak, Alexander, Varnai, Tamas | Land Use/Land Cover Classification | |
| Decadal changes in summer and autumn soil moisture drive dual shifts in | Anniwaer, Nazhakaiti, Li, Xiangyi, Xu, Hao, Wang, Kai, Zhu, Zaichun | Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | |
| ERA5-Land: soil moisture dry-downs detection over the Argentine Pampas | Beninato, Sabrina, Holzman, Mauro Ezequiel, Degano, Maria Florencia, Rivas, Raul Eduardo | Land Use/Land Cover Classification | |
| Dynamic Modeling of Ammonia Emissions and Nitrogen Deposition via Online Coupling of WRFChem and NoahMPCN | Cao, Yeer, Ren, Chuanhua, Zhang, Han, Wei, Zhongwang, Guo, Yixin, Cai, Xitian | Land Use/Land Cover Classification | |
| Enhancing Estimation of Fine Particulate Matter Chemical Composition across North America by Including Geophysical A Priori Information in Deep Learning with ... | Shen, Siyuan, van Donkelaar, Aaron, Jacobs, Nathan, Li, Chi, Martin, Randall V. | Land Use/Land Cover Classification | |
| Development of the long-term harmonized multi-satellite SIF (LHSIF) dataset at 0.05 resolution (19952024) | Zou, Chu, Du, Shanshan, Liu, Xinjie, Liu, Liangyun | Atmospheric Carbon Dioxide, Solar Induced Fluorescence, Land Use/Land Cover Classification, Reflectance, Primary Production, Chlorophyll, Photosynthesis, Leaf Characteristics, Albedo, Anisotropy | |
| Daily global transpiration estimation (2001-2018) by integrating | Jin, Jiaxin, Dong, Linan, Gan, Guojing, Fan, Xingwang, Wang, Ying, Zhu, Qiuan, Doughty, Russell, Qin, Yuanwei, Yang, Guishan | Surface Pressure, Heat Flux, Longwave Radiation, Shortwave Radiation, Surface Temperature, Humidity, Evapotranspiration, Surface Winds, Rain, Precipitation Rate, Snow, Soil Moisture/Water Content, Soil Temperature, Land Surface Temperature, Snow Water Equivalent, Runoff, Land Use/Land Cover Classification | |
| Evaporative cooling exceeded albedo-induced warming in greening areas of global drylands | Daramola, Mojolaoluwa T., Li, Renqiang, Xu, Ming | Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Emissivity, Land Surface Temperature | |
| Global daily 9 km remotely sensed soil moisture (20152025) with microwave radiative transfer-guided learning | Feng, Sijia, Li, Aoyang, Zhou, Rui, Butterbach-Bahl, Klaus, Guan, Kaiyu, Jin, Zhenong, Looms, Majken C., Wang, Sherrie, Igel, Christian, Treat, Claire, Olesen, Jrgen Eivind, Wang, Sheng | Brightness Temperature, Surface Soil Moisture, Air Temperature, Soil Moisture/Water Content, Soil Temperature, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Land Use/Land Cover Classification | |
| Global retrieval of harmonized microwave land surface emissivity | Hu, Jiheng, Li, Rui, Zhang, Peng, Wang, Yu, Wu, Shengli, Letu, Husi, Weng, Fuzhong | Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow, Atmospheric Water Vapor, Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Brightness Temperature, Snow Cover | |
| FoScenes: A high-fidelity, large-scale 3D forest plant area density product derived from open-access airborne lidar data | Zhou, Cailin, Yin, Tiangang, Wei, Shanshan, Cook, Bruce D., Tan, Weiwei, Yan, Wai Yeung, Chen, Qi, Gastellu-Etchegorry, Jean-Philippe | Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Land Use/Land Cover Classification | |
| Improving photosynthetic phenology detection by incorporating vegetation index with meteorological factors | Kuang, Yaning, Li, Zifan, Wei, Lixue, Tang, Dong, Mai, Yongjian, Yuan, Huanhuan, Zheng, Lei, Deng, Jianming, Peng, Jie | Land Use/Land Cover Classification | |
| Intensified seasonal droughts and carryover effects amplify negative growth anomalies in Eurasian grasslands during the past four decades | Anniwaer, Nazhakaiti, Chen, Jiana, Zhang, Yanan, Zhao, Weiqing, He, Yue, Wang, Kai, Cao, Sen, Zhu, Zaichun | Land Use/Land Cover Classification | |
| Interannual variability of spring dust column mass concentration over | Zhang, Hailiang, He, Qing, Aihaiti, Ailiyaer, Li, Yongkang, Zeng, Kang, Jiang, Hong, Liao, Qimei | Land Use/Land Cover Classification, Aerosols, Aerosol Extinction, Aerosol Optical Depth/Thickness, Angstrom Exponent, Aerosol Particle Properties, Carbonaceous Aerosols, Dust/Ash/Smoke, Organic Particles, Sulfate Particles, Sulfur Oxides, Sulfur Compounds, Sulfate, Sulfur Dioxide, Sulfur Oxides, Particulate Matter, Dimethyl Sulfide, Black Carbon, Sea Salt, PARTICULATE MATTER (PM 2.5), PARTICULATE MATTER (PM 10), PARTICULATE MATTER (PM 1.0), Emissions, UV Aerosol Index, Gas/Aerosol Composition, Deposition | |
| Increasing control of vapor pressure deficit on the end of the growing season in boreal forest | Wang, Meiyu, Zhao, Jianjun, Zhou, Yuyu, Zhang, Hongyan, Zhang, Zhengxiang, Xiong, Tao, Wang, Yeqiao | Land Use/Land Cover Classification | |
| Pantropical moist forests are converging towards a middle leaf longevity | Xue, Meimei, Yang, Xueqin, Chen, Xiuzhi, Ciais, Philippe, Zhou, Liming, Reich, Peter B., Xiao, Jingfeng, Li, Xing, Xiao, Xiangming, Green, Julia K., Chen, Jing Ming, Liu, Jane, Shang, Jiali, Luo, Xiangzhong, Tian, Jie, Liu, Hui, Zhu, Peng, Yan, Kai, Fu, Xinyue, Han, Liusheng, Yuan, Wenping, Wu, Chaoyang | Land Use/Land Cover Classification, Photosynthesis, Primary Production, VEGETATION PRODUCTIVITY, Total Surface Precipitation Rate | |
| Origins of precipitation in the world's water towers | Zhang, Bomei, Gao, Hongkai, WangErlandsson, Lan, Li, Yan | Land Use/Land Cover Classification | |
| Quantitative assessment of vegetation-driven removal of key air | Liu, Tong, Yao, Jiaqi, Cao, Yongqiang, Lu, Lijun, Chang, Huanyu, Ren, He, Mo, Fan, Wang, Xuan, Xu, Nan | 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, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Land Use/Land Cover Classification | |
| Quantifying glacier and snow shrinkage: future water stress in Northern Tien Shan, Central Asia | Zhao, Qiudong, Ding, Yongjian, Jin, Zizhen, Qin, Yan, He, Rui, Shangguan, Donghui, Zhang, Shiqiang, Chang, Yaping, Han, Haidong | Land Use/Land Cover Classification | |
| Monitoring Changes in Landsat Thermal Features in Urban and Non-Urban | Shi, Hua, Barber, Christopher P., Sayler, Kristi L., Smith, Kelcy, Hussain, Reza | Land Use/Land Cover Classification, Land Surface Temperature, Emissivity, Crop/Plant Yields, Land Use Classes, Landscape Patterns, Surface Radiative Properties | |
| The dynamic response of vegetation water use efficiency to wildfire | Xi, Huipeng, Wang, Qunming, Atkinson, Peter M. | Land Use/Land Cover Classification, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Fire Ecology, Biomass Burning, Wildfires, Fire Occurrence, Burned Area | |
| The influence of plant soil moisture stress on solar-induced chlorophyll fluorescence efficiency across Africa | Onkaew, Khomkrit, Quaife, Tristan, Black, Emily, Maidment, Ross I. | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Land Use/Land Cover Classification, Reflectance, Anisotropy, Albedo | |
| Seasonality changes in the terrestrial water cycle under different vegetation types and their attribution in the Songliao River Basin, Northeast China | Fei, Wenli, Shen, Lidu, Liang, Lin, Liu, Yage, Zhang, Yuan, Wang, Anzhi, Wu, Jiabing, Zhu, Ling, Cai, Rongrong, Lai, Jie | Land Use/Land Cover Classification | |
| Temperature and Moisture Variability Drive Resilience Shifts in Canada's | Yang, Chenlin, Cui, Tianxiang, Fan, Lei, Wang, Jian, Wigneron, Jean-Pierre | Land Use/Land Cover Classification, Land Surface Temperature, Emissivity, Fire Ecology, Biomass Burning, Wildfires, Fire Occurrence, Burned Area | |
| Spatiotemporal Patterns and Climate Attributions of Seasonal Stability of Vegetation Growth in Northern China | Liang, Juanzhu, Fan, Liping, Zhou, Yuke, Li, Wenfang | 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 |
|---|---|---|---|---|---|---|---|
| Land_Cover_Type_1_Percent | Percent cover of each IGBP class at each pixel | Percent | uint8 | 255 | 0 to 100 | N/A | N/A |
| Land_Cover_Type_2_Percent | Percent cover of each UMD class at each pixel | Percent | uint8 | 255 | 0 to 100 | N/A | N/A |
| Land_Cover_Type_3_Percent | Percent cover of each LAI class at each pixel | Percent | uint8 | 255 | 0 to 100 | N/A | N/A |
| Majority_Land_Cover_Type_1 | Most likely IGBP class for each 0.05 degree pixel | Class | uint8 | 255 | 0 to 16 | N/A | N/A |
| Majority_Land_Cover_Type_1_Assessment | Majority IGBP class confidence | Percent | uint8 | 255 | 0 to 100 | N/A | N/A |
| Majority_Land_Cover_Type_2 | Most likely UMD class for each 0.05 degree pixel | Class | uint8 | 255 | 0 to 15 | N/A | N/A |
| Majority_Land_Cover_Type_2_Assessment | Majority UMD class confidence (filled with land/water mask) | Percent | uint8 | 255 | 0 to 100 | N/A | N/A |
| Majority_Land_Cover_Type_3 | Most likely LAI class for each 0.05 degree pixel | Class | uint8 | 255 | 0 to 10 | N/A | N/A |
| Majority_Land_Cover_Type_3_Assessment | Majority LAI class confidence (filled with land/water mask) | Percent | uint8 | 255 | 0 to 100 | N/A | N/A |