N: 90 S: -90 E: 180 W: -180
Description
The MCD19A3 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the MCD19A3 Version 6.1 data product.
The MCD19A3 Version 6 data product is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Multi-angle Implementation of Atmospheric Correction (MAIAC) Bidirectional Reflectance Distribution Function (BRDF) Model Parameters gridded Level 3 product which is output every 8 days at 1 kilometer resolution. The MCD19A3 product provides three coefficients (weights) of the RossThick/Li-Sparse (RTLS) BRDF model that can be used to describe the anisotropy of each pixel. The retrievals represent cloud-free and low aerosol conditions.
The MCD19A3 BRDF Model Parameters product contains the following Science Dataset (SDS) layers: RTLS isotropic kernel parameter (Kiso) for bands 1-8, the RTLS volumetric kernel parameter (Kvol) for bands 1-8, RTLS geometric kernel parameter (Kgeo) for bands 1-8, surface albedo for bands 1-8, and the number of days since last update to current day. Three low-resolution browse images are also included showing the BRDF coefficients for the red band: (1) Kiso, (2) Kvol, and (3) Kgeo.
Known Issues
- Due to Terra MODIS calibration degradation, BRDF in MODIS Band 8 may contain artifacts (e.g., 10 km striping), particularly after 2015.
- Known issues are described on page 14 of the User Guide.
- For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.
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.
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File Naming Convention
The file name begins with the Product Short Name (MCD19A3) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2002273), the Tile Identifier which is horizontal tile and vertical tile provided as hXXvYY (h01v11), the Version of the data collection (006), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2018017060405), 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 |
|---|---|---|---|
| Satellite Multi-Angle Observations of Wildfire Smoke Plumes During the | Noyes, K. T. Junghenn, Kahn, R. A. | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES, Reflectance | |
| MAGARA: A Multi-Angle Geostationary Aerosol Retrieval Algorithm | Limbacher, James A., Kahn, Ralph A., Friberg, Mariel D., Lee, Jaehwa, Summers, Tyler, Zhang, Hai | Reflectance | |
| Improved detection of abrupt change in vegetation reveals dominant fractional woody cover decline in Eastern Africa | Abera, Temesgen Alemayehu, Heiskanen, Janne, Maeda, Eduardo Eiji, Hailu, Binyam Tesfaw, Pellikka, Petri K.E. | Reflectance, Anisotropy, Canopy Characteristics, Evergreen Vegetation, Crown, Deciduous Vegetation, Leaf Characteristics, Vegetation Cover, Land Use/Land Cover Classification, Population Density, Fire Ecology, Biomass Burning, Wildfires, Fire Occurrence, Burned Area | |
| The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over ... | Limbacher, James A., Kahn, Ralph A., Lee, Jaehwa | Reflectance | |
| Comparison of different methods of determining land surface reflectance for AOD retrieval | Wang, Qingxin, Du, Dongsheng, Li, Siwei, Yang, Jie, Lin, Hao, Du, Juan | Aerosol Optical Depth/Thickness, Reflectance | |
| Assessment of the vertical distribution of speciated aerosol absorption over South Asia using spaceborne LIDAR and ground-based observations | Lakshmi, N.B., Nair, Vijayakumar S., Babu, S. Suresh | Reflectance, Atmospheric Ozone | |
| Nighttime smoke aerosol optical depth over U.S. rural areasFirst retrieval from VIIRS moonlight observations | Zhou, Meng, Wang, Jun, Chen, Xi, Xu, Xiaoguang, Colarco, Peter R., Miller, Steven D., Reid, Jeffrey S., Kondragunta, Shobha, Giles, David Matthew, Holben, Brent | Aerosol Optical Depth/Thickness, Reflectance, Geopotential Height, Atmospheric Ozone, Pressure Thickness, Sea Level Pressure, Surface Pressure, Air Temperature, Upper Air Temperature, Atmospheric Water Vapor, Cloud Liquid Water/Ice, Cloud Fraction, U/V Wind Components, U/V Wind Components, Ozone Profiles | |
| Prospects for Long-Term Agriculture in Southern Africa: Emergent | Wei, Tiffany M., Barros, Ana P. | Aerosol Optical Depth/Thickness, Land Use/Land Cover Classification, Surface Pressure, Heat Flux, Longwave Radiation, Shortwave Radiation, Air Temperature, Specific Humidity, Evapotranspiration, Wind Speed, Rain, Snow, Soil Moisture/Water Content, Soil Temperature, Land Surface Temperature, Snow Cover, Snow Depth, Snow Water Equivalent, Runoff, Reflectance, Anisotropy, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Albedo, Precipitation, Precipitation Amount, Precipitation Rate, Emissivity | |
| Retrieval and validation of AOD from himawari-8 data over Bohai Rim region, China | Wang, Qingxin, Li, Siwei, Zeng, Qiaolin, Sun, Lin, Yang, Jie, Lin, Hao | Reflectance | |
| First Provisional Land Surface Reflectance Product from Geostationary | Li, Shuang, Wang, Weile, Hashimoto, Hirofumi, Xiong, Jun, Vandal, Thomas, Yao, Jing, Qian, Lexiang, Ichii, Kazuhito, Lyapustin, Alexei, Wang, Yujie, Nemani, Ramakrishna | Aerosol Optical Depth/Thickness, Reflectance, Snow Grain Size, Snow Cover | |
| Effects of light component and water stress on photosynthesis of Amazon rainforests during the 2015/2016 El Nino drought | Yan, Hao, Wang, Shaoqiang, Huete, Alfredo, Shugart, Herman H. | Albedo, Anisotropy, Reflectance, Total Surface Precipitation Rate | |
| MODIS collection 6 MAIAC algorithm | Lyapustin, Alexei, Wang, Yujie, Korkin, Sergey, Huang, Dong | Aerosol Optical Depth/Thickness, Reflectance, Snow Grain Size, Snow Cover |
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 |
|---|---|---|---|---|---|---|---|
| Kgeo | RTLS geometric kernel parameter for bands 1-8 | N/A | int16 | -32767 | -32766 to 32767 | 0.0001 | N/A |
| Kiso | RTLS isotropic kernel parameter for bands 1-8 | N/A | int16 | -32767 | -32766 to 32767 | 0.0001 | N/A |
| Kvol | RTLS volumetric kernel parameter for bands 1-8 | N/A | int16 | -32767 | -32766 to 32767 | 0.0001 | N/A |
| Sur_albedo | Surface albedo for bands 1-8 | N/A | int16 | -28672 | -100 to 16000 | 0.0001 | N/A |
| UpdateDay | Number of days since last update to the current day | N/A | uint8 | 255 | 0 to 254 | N/A | N/A |