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Description

The MCD43A4 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the MCD43A4 Version 6.1 data product.

The Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A4 Version 6 Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) dataset is produced daily using 16 days of Terra and Aqua MODIS data at 500 meter (m) resolution. The view angle effects are removed from the directional reflectances, resulting in a stable and consistent NBAR product. Data are temporally weighted to the ninth day which is reflected in the Julian date in the file name.

Users are urged to use the band specific quality flags to isolate the highest quality full inversion results for their own science applications as described in the User Guide.

The MCD43A4 provides NBAR and simplified mandatory quality layers for MODIS bands 1 through 7. Essential quality information provided in the corresponding MCD43A2 data file should be consulted when using this product.

Known Issues

  • The incorrect representation of the aerosol quantities (low average high) in the C6 MYD09 and MOD09 surface reflectance products may have impacted downstream products particularly over arid bright surfaces. This (and a few other issues) have been corrected for C6.1. Therefore users should avoid substantive use of the C6 MCD43 products and wait for the C6.1 products. In any event, users are always strongly encouraged to download and use the extensive QA data provided in MCD43A2, in addition to the briefer mandatory QAs provided as part of the MCD43A1, 3, and 4 products.
  • Corrections were implemented in Collection 6.1 reprocessing.
  • For complete information about the MCD43A4 known issues refer to the MODIS Land Quality Assessment website.

Version Description

The following changes and improvements were implemented for inputs to MODIS Version 6 BRDF/Albedo Parameter data products: (1) Observations are weighted to estimate the BRDF/Albedo on the ninth day of the 16-day period, (2) Products utilize the snow status weighted to the ninth day, (3) Enhanced quality at high latitudes achieved through the utilization of all available observations during the acquisition period, (4) Products utilize L2G-lite surface reflectance as input, and (5) In instances where there are insufficient high-quality reflectances, a database containing archetypal BRDF parameters is employed to supplement the observational data and perform a lower-quality magnitude inversion.

Product Summary

Platforms
Terra ,
Aqua
Instruments
MODIS
Projects
TERRA ,
Aqua
Spatial Extent

N: 90 S: -90 E: 180 W: -180

Spatial Resolution
500 Meters x 500 Meters
Spatial Reference System(s)
MODIS Sinusoidal Tiling System
Location
GLOBAL
Coordinate System
CARTESIAN
Granule Spatial Representation
GEODETIC
Temporal Extent
2000-02-16 to 2023-02-17
Temporal Resolution
1 Day
Data Partner
Land Processes Distributed Active Archive Center (LP DAAC) ,
School for the Environment, University of Massachusetts, Boston (UMASS-B/SFE) ,
MODIS Adaptive Processing System, Terrestrial Information Systems Laboratory, Earth Sciences Division, Science and Exploration Directorate, Goddard Space Flight Center, NASA (NASA/GSFC/SED/ESD/TISL/MODAPS)
Concept ID
C2763289471-LPCLOUD
Data State
DEPRECATED
Number of Files/Granules
0
Processing Level
3
Published
Updated
Science Keywords
Reflectance ,
Anisotropy

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

Schaaf, C., & Wang, Z. (2015). MCD43A4 MODIS/Terra+Aqua BRDF/Albedo Nadir BRDF Adjusted Ref Daily L3 Global - 500m V006 [Dataset]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/MODIS/MCD43A4.006 Date Accessed: 2026-08-10

File Naming Convention

MCD43A4.A2002272.h16v16.006.2016132202805.hdf

The file name begins with the Product Short Name (MCD43A4) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2002272), the Tile Identifier which is horizontal tile and vertical tile provided as hXXvYY (h16v16), the Version of the data collection (006), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2016132202805), and the Data Format (hdf).

Documents

Publications Citing This Dataset

Filters
Title Year Author Topic
Baseline high-resolution maps of soil nutrients in Morocco to support sustainable agriculture Bouslihim, Yassine, Bouasria, Abdelkrim, Jelloul, Ahmed, Khiari, Lotfi, Dahhani, Sara, Mrabet, Rachid, Moussadek, Rachid Reflectance, Anisotropy
Comprehensive reassessment of Australia's land-surface phenology trends Burton, Chad.A., Rifai, Sami.W., Renzullo, Luigi.J., Van Dijk, Albert.I.J.M. Reflectance, Anisotropy
Detection of fast-changing intra-seasonal vegetation dynamics of drylands using solar-induced chlorophyll fluorescence (SIF) Wen, Jiaming, Tagliabue, Giulia, Rossini, Micol, Fava, Francesco Pietro, Panigada, Cinzia, Merbold, Lutz, Leitner, Sonja, Sun, Ying Longwave Radiation, Shortwave Radiation, Heat Flux, Liquid Precipitation, Snow/Ice, Geopotential Height, Altitude, Surface Temperature, Skin 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, Reflectance, Anisotropy, Land Use/Land Cover Classification, Solar Induced Fluorescence, Chlorophyll, Primary Production, Leaf Characteristics, Potential Vorticity, Vertical Profiles, Relative Humidity, Ozone Profiles
Crop water origins and hydroclimate vulnerability of global croplands Jiang, Yan, Burney, Jennifer A. Reflectance, Anisotropy, Vegetation Cover, Cropland
Ecosystem carbon use efficiency at global scale from upscaling eddy-covariance data with machine learning and MODIS products Campos-Taberner, M., Gilabert, M. A., Sanchez-Ruiz, S., Martinez, B., Jimenez-Guisado, A., Garcia-Haro, F. J. Land Use/Land Cover Classification, Evapotranspiration, Latent Heat Flux, Reflectance, Anisotropy, Photosynthesis, Primary Production, Vegetation Productivity, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar)
Coupling Remote Sensing With a Process Model for the Simulation of Xia, Yushu, Sanderman, Jonathan, Watts, Jennifer D., Machmuller, Megan B., Mullen, Andrew L., Rivard, Charlotte, Endsley, Arthur, Hernandez, Haydee, Kimball, John, Ewing, Stephanie A., Litvak, Marcy, Duman, Tomer, Krishnan, Praveena, Meyers, Tilden, Brunsell, Nathaniel A., Mohanty, Binayak, Liu, Heping, Gao, Zhongming, Chen, Jiquan, Abraha, Michael, Scott, Russell L., Flerchinger, Gerald N., Clark, Patrick E., Stoy, Paul C., Khan, Anam M., Brookshire, E. N. Jack, Zhang, Quan, Cook, David R., Thienelt, Thomas, Mitra, Bhaskar, MauritzTozer, Marguerite, Tweedie, Craig E., Torn, Margaret S., Billesbach, Dave Reflectance, Anisotropy, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Precipitation Amount, Maximum/Minimum Temperature, Shortwave Radiation, Snow Water Equivalent, Vapor Pressure
Contrasting age-dependent leaf acclimation strategies drive vegetation greening across deciduous broadleaf forests in mid-to high latitudes Wang, Fangyi, Xue, Meimei, Zhou, Liming, Doughty, Christopher E., Ciais, Philippe, Reich, Peter B., Shang, Jiali, Chen, Jing Ming, Liu, Jane, Green, Julia K., Hao, Dalei, Tao, Shengli, Su, Yanjun, Liu, Lingli, Xia, Jianyang, Wang, Han, Yu, Kailiang, Zhu, Zaichun, Zhu, Peng, Li, Xing, Liu, Hui, Zeng, Yelu, Yan, Kai, Liu, Liyang, Lafortezza, Raffaele, Su, Yongxian, Meng, Yanqiong, Pan, Yixuan, Yang, Xueqin, Fu, Yongshuo H., He, Nianpeng, Yuan, Wenping, Chen, Xiuzhi Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Plant Phenology, Reflectance, Anisotropy
Global phenology maps reveal the drivers and effects of seasonal asynchrony Terasaki Hart, Drew E., Bui, Thao-Nguyen, Di Maggio, Lauren, Wang, Ian J. Plant Phenology, Enhanced Vegetation Index (EVI), Reflectance, Anisotropy, Land Use/Land Cover Classification
Improving terrestrial solar-induced chlorophyll fluorescence (SIF) reconstruction through multi-satellite-derived SIF integration: a comparative study in regional scale Pan, Mengting, Lin, Xiaofeng, Xiao, Zhongyong, Wang, Fei, Guo, Lifeng, Wang, Cuiping, Xie, Jinghan, Fang, Jingchun Atmospheric Carbon Dioxide, Solar Induced Fluorescence, Reflectance, Anisotropy, Primary Production, Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Gross Primary Production (gpp)
Mature forest habitat mitigates the decline of an endangered greater Cally, Justin G., Macak, Phoebe V., Chick, Matt P., Blake, Brad, Wagner, Benjamin, Ramsey, David S.L. Reflectance, Anisotropy
Large-scale diurnal responses of solar-induced chlorophyll fluorescence Zhao, Dayang, Zhang, Zhaoying, Zhang, Yongguang Land Use/Land Cover Classification, Reflectance, Anisotropy, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Plant Phenology, Enhanced Vegetation Index (EVI)
Learning county from pixels: corn yield prediction with Wang, Xiaoyu, Ma, Yuchi, Xu, Yijia, Huang, Qunying, Yang, Zhengwei, Zhang, Zhou Reflectance, Anisotropy
Mapping global leaf inclination angle (LIA) based on field measurement data Li, Sijia, Fang, Hongliang Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Leaf Characteristics, Photosynthetically Active Radiation, Reflectance, Anisotropy
Machine learning-based winter wheat yield prediction using multisource Khosravani Shariati, Seyed Arash, Abbasi, Ali 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, Reflectance, Anisotropy, Emissivity, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar)
Quantifying shortwave radiative forcing and heating rates of UTLS Santhosh, V.N., Madhavan, B.L., Ratnam, M. Venkat Reflectance, Anisotropy
Quantifying the impact of air pollution from coal-fired electricity generation on crop productivity in India Singh, Kirat, Lobell, David B., Azevedo, Ines M. L. Reflectance, Anisotropy
Quantifying the impact of urban geometry on the urban albedo: A Zhou, Hongyan, Chen, Guanwen, Mei, Shuojun, Hang, Jian, Aktas, Yasemin D., Yang, Xinyan, Wang, Kai 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, Reflectance, Anisotropy
On the added value of sequential deep learning for the upscaling of evapotranspiration Kraft, Basil, Nelson, Jacob A., Walther, Sophia, Gans, Fabian, Weber, Ulrich, Duveiller, Gregory, Reichstein, Markus, Zhang, Weijie, Ruwurm, Marc, Tuia, Devis, Korner, Marco, Hamdi, Zayd, Jung, Martin Reflectance, Anisotropy, Land Surface Temperature, Emissivity, Albedo
PSNet: A deep learning framework following hierarchical yield level Zhong, Renhai, Xiong, Xingguo, Tian, Qiyu, Huang, Jingfeng, Zhu, Linchao, Yang, Yi, Lin, Tao Reflectance, Anisotropy
Modification and Comparison of Two Urban Vegetation Models Over Southern MadsenColford, Sabrina, Hutyra, Lucy, Smith, Ian, Wu, Dien, Arain, M. Altaf, Staebler, Ralf, Ma, William, RestrepoCoupe, Natalia, Wunch, Debra Land Use/Land Cover Classification, Plant Phenology, Enhanced Vegetation Index (EVI), Reflectance, Urban Lands, Land Use/Land Cover, Urbanization/Urban Sprawl, Infrastructure, Anisotropy
Spatiotemporal variation of spring phenology and the corresponding scale Zhu, Chongjing, She, Xiaojun, Gao, Xiaojie, Huang, Yajun, Zeng, Yelu, Ding, Chao, Fu, Dongjie, Shao, Jing, Li, Yao Reflectance, Anisotropy, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Land Use/Land Cover Classification
Resistance of grassland productivity to drought and heatwave over a temperate semi-arid climate zone Huang, Yangbin, Lei, Huimin, Duan, Limin Reflectance, Anisotropy
Using automated machine learning for the upscaling of gross primary productivity Gaber, Max, Kang, Yanghui, Schurgers, Guy, Keenan, Trevor Land Use/Land Cover Classification, Land Surface Temperature, Emissivity, Photosynthetically Active Radiation, Leaf Area Index (LAI), Leaf Characteristics, Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Reflectance, Anisotropy, Primary Production, Gross Primary Production (gpp)
Using phenology to unravel differential soil water use and productivity in a semiarid savanna Steiner, Blake, Scott, Russell L., Hu, Jia, MacBean, Natasha, Richardson, Andrew, Moore, David J. P. Reflectance, Anisotropy
X-BASE: the first terrestrial carbon and water flux products from an Nelson, Jacob A., Walther, Sophia, Gans, Fabian, Kraft, Basil, Weber, Ulrich, Novick, Kimberly, Buchmann, Nina, Migliavacca, Mirco, Wohlfahrt, Georg, Sigut, Ladislav, Ibrom, Andreas, Papale, Dario, Gockede, Mathias, Duveiller, Gregory, Knohl, Alexander, Hortnagl, Lukas, Scott, Russell L., Dusek, Jiri, Zhang, Weijie, Hamdi, Zayd Mahmoud, Reichstein, Markus, Aranda-Barranco, Sergio, Ardo, Jonas, Op de Beeck, Maarten, Billesbach, Dave, Bowling, David, Bracho, Rosvel, Brummer, Christian, Camps-Valls, Gustau, Chen, Shiping, Cleverly, Jamie Rose, Desai, Ankur, Dong, Gang, El-Madany, Tarek S., Euskirchen, Eugenie Susanne, Feigenwinter, Iris, Galvagno, Marta, Gerosa, Giacomo A., Gielen, Bert, Goded, Ignacio, Goslee, Sarah, Gough, Christopher Michael, Heinesch, Bernard, Ichii, Kazuhito, Jackowicz-Korczynski, Marcin Antoni, Klosterhalfen, Anne, Knox, Sara, Kobayashi, Hideki, Kohonen, Kukka-Maaria, Korkiakoski, Mika, Mammarella, Ivan, Gharun, Mana, Marzuoli, Riccardo, Matamala, Roser, Metzger, Stefan, Montagnani, Leonardo, Nicolini, Giacomo, O'Halloran, Thomas, Ourcival, Jean-Marc, Peichl, Matthias, Pendall, Elise, Ruiz Reverter, Borja, Roland, Marilyn, Sabbatini, Simone, Sachs, Torsten, Schmidt, Marius, Schwalm, Christopher R., Shekhar, Ankit, Silberstein, Richard, Silveira, Maria Lucia, Spano, Donatella, Tagesson, Torbern, Tramontana, Gianluca, Trotta, Carlo, Turco, Fabio, Vesala, Timo, Vincke, Caroline, Vitale, Domenico, Vivoni, Enrique R., Wang, Yi, Woodgate, William, Yepez, Enrico A., Zhang, Junhui, Zona, Donatella, Jung, Martin Carbonaceous Aerosols, Nitrogen Oxides, Particulates, Hydrogen Cyanide, Emissions, Non-methane Hydrocarbons/Volatile Organic Compounds, Particulate Matter, Fire Occurrence, Nitrogen Oxides, Sulfur Dioxide, Carbon And Hydrocarbon Compounds, Emissivity, Land Surface Temperature, Reflectance, Anisotropy, Albedo, Land Use/Land Cover Classification
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