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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 [Data set]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/MODIS/MCD43A4.006 Date Accessed: 2026-06-05

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
Assessment of the efficiency of using MODIS MCD43A4 in mapping of rice planting calendar in the Mekong delta Diem, P K, Diem, N K, Hung, H V Reflectance, Anisotropy
Identifying and understanding alternative states of dryland landscape: A hierarchical analysis of time series of fractional vegetation-soil nexuses in China's Hexi Corridor Sun, Qiangqiang, Zhang, Ping, Jiao, Xin, Han, Wenchao, Sun, Yanan, Sun, Danfeng Land Use/Land Cover Classification, Terrain Elevation, Digital Elevation/Terrain Model (DEM), Topographical Relief Maps, Reflectance, Anisotropy
Identifying Basal Nighttime Radiance Levels for Estimating Traffic Flow based on VIIRS/DNB data Bragion, Gabriel da Rocha, Goncalves, Gabriel Crivellaro, DalAsta, Ana Paula, Santos, Ana Carolina de Faria, Oliveira, Lucas Maia de, Monteiro, Antonio Miguel Vieira, Amaral, Silvana Reflectance, Anisotropy
Hybrid phenology matching model for robust crop phenological retrieval Diao, Chunyuan, Yang, Zijun, Gao, Feng, Zhang, Xiaoyang, Yang, Zhengwei Reflectance, Anisotropy, Land Surface Temperature, Emissivity
Human footprint and protected areas shape elephant range across Africa Wall, Jake, Wittemyer, George, Klinkenberg, Brian, LeMay, Valerie, Blake, Stephen, Strindberg, Samantha, Henley, Michelle, Vollrath, Fritz, Maisels, Fiona, Ferwerda, Jelle, Douglas-Hamilton, Iain Reflectance, Anisotropy, Canopy Characteristics, Evergreen Vegetation, Crown, Deciduous Vegetation, Leaf Characteristics, Vegetation Cover, Land Use/Land Cover Classification, Land Surface Temperature, Emissivity
Integrating remotely sensed fuel variables into wildfire danger assessment for China Quan, Xingwen, Xie, Qian, He, Binbin, Luo, Kaiwei, Liu, Xiangzhuo Land Use/Land Cover Classification, Reflectance, Anisotropy, Fire Ecology, Biomass Burning, Wildfires, Fire Occurrence, Burned Area
Live fuel moisture content estimation from MODIS: A deep learning Zhu, Liujun, Webb, Geoffrey I., Yebra, Marta, Scortechini, Gianluca, Miller, Lynn, Petitjean, Francois Terrain Elevation, Digital Elevation/Terrain Model (DEM), Topographical Relief Maps, Reflectance, Anisotropy
Local climatic and environmental effects of an onshore wind farm in North China Luo, Lihui, Zhuang, Yanli, Duan, Quntao, Dong, Longxiang, Yu, Ye, Liu, Yonghong, Chen, Keren, Gao, Xiaoqing Reflectance, Anisotropy, Land Surface Temperature, Emissivity, Evapotranspiration, Latent Heat Flux
Making Landsat 5, 7 and 8 reflectance consistent using MODIS nadir-BRDF adjusted reflectance as reference Che, Xianghong, Zhang, Hankui K., Liu, Jiping Reflectance, Anisotropy, Albedo
Land cover composition, climate, and topography drive land surface phenology in a recently burned landscape: An application of machine learning in phenological ... Wang, Jianmin, Zhang, Xiaoyang, Rodman, Kyle Reflectance, Anisotropy, RADAR IMAGERY, Terrain Elevation, Topographical Relief Maps, Digital Elevation/Terrain Model (DEM), Albedo
Interannual variations of vegetation optical depth are due to both water stress and biomass changes Konings, Alexandra G., Holtzman, Nataniel M., Rao, Krishna, Xu, Liang, Saatchi, Sassan S. Reflectance, Anisotropy, Land Use/Land Cover Classification, Land Surface Temperature, Emissivity
Is Alaska's YukonKuskokwim Delta Greening or Browning? Resolving Mixed Signals of Tundra Vegetation Dynamics and Drivers in the Maritime Arctic Frost, Gerald V., Bhatt, Uma S., Macander, Matthew J., Hendricks, Amy S., Jorgenson, M. Torre Reflectance, Anisotropy, RIVER/LAKE ICE BREAKUP, River Ice Depth/Extent, Plant Phenological Changes, Snow Depth, Range Changes, Vegetation Species, Rural Areas, Conservation, Vulnerable Populations, Use/Feeding Habitats
Influence of varying solar zenith angles on land surface phenology derived from vegetation indicesA case study in the harvard forest Li, Yang, Jiao, Ziti, Zhao, Kaiguang, Dong, Yadong, Zhou, Yuyu, Zeng, Yelu, Xu, Haiqing, Zhang, Xiaoning, Hu, Tongxi, Cui, Lei Reflectance, Anisotropy, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Albedo
Improving the accuracy of spring phenology detection by optimally smoothing satellite vegetation index time series based on local cloud frequency Tian, Jiaqi, Zhu, Xiaolin, Chen, Jin, Wang, Cong, Shen, Miaogen, Yang, Wei, Tan, Xiaoyue, Xu, Shuai, Li, Zhilin Reflectance, Anisotropy, Plant Phenology, Enhanced Vegetation Index (EVI), Emissivity, Land Surface Temperature
Effects of meteorological parameters on surface water loss in burdur lake, turkey over 34 years Landsat google earth engine time-series Abujayyab, Sohaib K. M., Almotairi, Khaled H., Alswaitti, Mohammed, Amr, Salem S. Abu, Alkarkhi, Abbas F. M., Tasoglu, Enes, Hussein, Ahmad MohdAziz Reflectance, Anisotropy
ECOSTRESS estimates gross primary production with fine spatial resolution for different times of day from the International Space Station Li, Xing, Xiao, Jingfeng, Fisher, Joshua B., Baldocchi, Dennis D. Land Use/Land Cover Classification, Reflectance, Anisotropy, Land Surface Temperature, Emissivity, Clouds
Development of a global annual land surface phenology dataset for 1982-2018 from the AVHRR data by implementing multiple phenology retrieving methods Wu, Wei, Sun, Ying, Xiao, Kun, Xin, Qinchuan Land Use/Land Cover Classification, Reflectance, Anisotropy, Plant Phenology, Enhanced Vegetation Index (EVI)
Estimation of pixel-level seismic vulnerability of the building environment based on mid-resolution optical remote sensing images Fan, Xiwei, Nie, Gaozhong, Xia, Chaoxu, Zhou, Junxue Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Reflectance, Anisotropy
Estimation of dry vegetation cover and mass from MODIS data: Wu, Jing, Kurosaki, Yasunori, Gantsetseg, Batdelger, Ishizuka, Masahide, Sekiyama, Tsuyoshi Thomas, Buyantogtokh, Batjargal, Liu, Jiaqi Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Reflectance, Anisotropy
Corn biomass estimation by integrating remote sensing and long-term observation data based on machine learning techniques Geng, Liying, Che, Tao, Ma, Mingguo, Tan, Junlei, Wang, Haibo Reflectance, Anisotropy
Corn yield prediction and uncertainty analysis based on remotely sensed variables using a Bayesian neural network approach Ma, Yuchi, Zhang, Zhou, Kang, Yanghui, Ozdogan, Mutlu Land Use/Land Cover Classification, Reflectance, Anisotropy, Land Surface Temperature, Emissivity
Divergent processes and trends of desertification in Inner Mongolia and Mongolia Guo, Xiaona, Chen, Ruishan, Thomas, David S.G., Li, Qiang, Xia, Zilong, Pan, Zhenzhen Reflectance, Anisotropy
Diurnal and seasonal trends and associated determinants of surface urban heat islands in large Bangladesh cities Dewan, Ashraf, Kiselev, Grigory, Botje, Dirk Albedo, Anisotropy, Reflectance, Land Surface Temperature, Emissivity, Land Use/Land Cover Classification, Snow Grain Size, Snow Cover
Detecting recent crop phenology dynamics in corn and soybean cropping systems of Kentucky Yang, Yanjun, Tao, Bo, Liang, Liang, Huang, Yawen, Matocha, Chris, Lee, Chad D., Sama, Michael, Masri, Bassil El, Ren, Wei Reflectance, Anisotropy
Estimating evapotranspiration based on the satellite-retrieved near-infrared reflectance of vegetation (NIRv) over croplands Tang, Lili, Zhang, Sha, Zhang, Jiahua, Liu, Yan, Bai, Yun Land Use/Land Cover Classification, Reflectance, Anisotropy, Land Surface Temperature, Emissivity
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