N: 90 S: -90 E: 180 W: -180
Error message
The submitted value 10 in the Items element is not allowed.Description
The Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A4 Version 6.1 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
- 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.
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File Naming Convention
The file name begins with the Product Short Name (MCD43A4) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2025212), the Tile Identifier which is horizontal tile and vertical tile provided as hXXvYY (h04v10), the Version of the data collection (061), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2025221032559), 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 |
|---|---|---|---|
| Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics | Wang, Xian, Biederman, Joel A., Knowles, John F., Scott, Russell L., Turner, Alexander J., Dannenberg, Matthew P., Kohler, Philipp, Frankenberg, Christian, Litvak, Marcy E., Flerchinger, Gerald N., Law, Beverly E., Kwon, Hyojung, Reed, Sasha C., Parton, William J., Barron-Gafford, Greg A., Smith, William K. | Reflectance, Anisotropy | |
| Spatiotemporal remote sensing image fusion using multiscale two-stream convolutional neural networks | Chen, Yuehong, Shi, Kaixin, Ge, Yong, Zhou, Ya'nan | Reflectance, Anisotropy | |
| Spatiotemporal fusion modelling using STARFMExamples of Landsat 8 and Sentinel-2 NDVI in Bavaria | Dhillon, Maninder Singh, Dahms, Thorsten, Kubert-Flock, Carina, Steffan-Dewenter, Ingolf, Zhang, Jie, Ullmann, Tobias | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Reflectance, Anisotropy | |
| Quantification of Urban Forest and Grassland Carbon Fluxes Using Field Measurements and a SatelliteBased Model in Washington DC/Baltimore Area | Winbourne, J. B., Smith, I. A., Stoynova, H., Kohler, C., Gately, C. K., Logan, B. A., Reblin, J., Reinmann, A., Allen, D. W., Hutyra, L. R. | Reflectance, Anisotropy | |
| TROPOMI SIF reveals large uncertainty in estimating the end of plant growing season from vegetation indices data in the Tibetan Plateau | Yang, Jilin, Xiao, Xiangming, Doughty, Russell, Zhao, Miaomiao, Zhang, Yao, Kohler, Philipp, Wu, Xiaocui, Frankenberg, Christian, Dong, Jinwei | Reflectance, Anisotropy, Land Use/Land Cover Classification, Albedo | |
| Thirty-eight years of CO2 fertilization has outpaced growing aridity to drive greening of Australian woody ecosystems | Rifai, Sami W., De Kauwe, Martin G., Ukkola, Anna M., Cernusak, Lucas A., Meir, Patrick, Medlyn, Belinda E., Pitman, Andy J. | Reflectance, Anisotropy, Canopy Characteristics, Evergreen Vegetation, Crown, Deciduous Vegetation, Leaf Characteristics, Vegetation Cover, Land Use/Land Cover Classification, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar) | |
| The restoration potential of the grasslands on the Tibetan Plateau | Wang, Ruijing, Feng, Qisheng, Jin, Zheren, Liang, Tiangang | Reflectance, Anisotropy, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | |
| An exploration of solar-induced chlorophyll fluorescence (SIF) factors simulated by SCOPE for capturing GPP across vegetation types | Yang, Songxi, Yang, Jian, Shi, Shuo, Song, Shalei, Zhang, Yangyang, Luo, Yi, Du, Lin | Reflectance, Anisotropy, 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, Geopotential Height, Atmospheric Ozone, Pressure Thickness, Sea Level Pressure, Surface Pressure, Upper Air Temperature, Atmospheric Water Vapor, Cloud Liquid Water/Ice, Cloud Fraction, U/V Wind Components, Ozone Profiles, Photosynthesis, Primary Production, Vegetation Productivity, Atmospheric Radiation, Longwave Radiation, Shortwave Radiation, Radiative Flux, Radiative Forcing, Surface Radiative Properties, Albedo, Emissivity, Cloud Properties, Cloud Optical Depth/Thickness, Skin Temperature, Sea Surface Skin Temperature, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar) | |
| Satellite observed vegetation dynamics and drivers in the Namib sand sea over the recent 20 years | Qiao, Na, Wang, Lixin | Reflectance, Anisotropy, Albedo, Total Surface Precipitation Rate | |
| 2017 Ventenata dubia distribution in the Blue Mountains Ecoregion of Oregon, Washington, and Idaho - probability | Nietupski, Ty C., Kerns, Becky K. | Reflectance, Anisotropy | |
| A unified vegetation index for quantifying the terrestrial biosphere | Camps-Valls, Gustau, Campos-Taberner, Manuel, Moreno-Martinez, Alvaro, Walther, Sophia, Duveiller, Gregory, Cescatti, Alessandro, Mahecha, Miguel D., Munoz-Mari, Jordi, Garcia-Haro, Francisco Javier, Guanter, Luis, Jung, Martin, Gamon, John A., Reichstein, Markus, Running, Steven W. | Reflectance, Anisotropy, Albedo | |
| Adaptive drift and barrier-avoidance by a fly-forage migrant along a | Vansteelant, Wouter M.G., Gangoso, Laura, Bouten, Willem, Viana, Duarte S., Figuerola, Jordi | Reflectance, Anisotropy | |
| Adopting differenceindifferences method to monitor crop response to agrometeorological hazards with satellite dataA case study of dryhot wind | Wang, Shuai, Rao, Yuhan, Chen, Jin, Liu, Licong, Wang, Wenqing | Reflectance, Anisotropy | |
| An improved cloud gap-filling method for longwave infrared land surface temperatures through introducing passive microwave techniques | Dowling, Thomas P. F., Song, Peilin, Jong, Mark C. De, Merbold, Lutz, Wooster, Martin J., Huang, Jingfeng, Zhang, Yongqiang | Reflectance, Anisotropy, Land Surface Temperature, Emissivity | |
| An adaptive adversarial domain adaptation approach for corn yield | Ma, Yuchi, Zhang, Zhou, Yang, Hsiuhan Lexie, Yang, Zhengwei | Reflectance, Anisotropy | |
| An Algorithm for the Retrieval of High Temporal-Spatial Resolution | Yang, Gang, Wang, Jiyan, Xiong, Junnan, Yong, Zhiwei, Ye, Chongchong, Sun, Huaizhang, Liu, Jun, Duan, Yu, He, Yufeng, He, Wen | Reflectance, Anisotropy, Albedo | |
| An effective method for generating spatiotemporally continuous 30 m vegetation products | Li, Xiuxia, Liang, Shunlin, Jin, Huaan | Reflectance, Anisotropy | |
| Assessing the effects of time interpolation of NDVI composites on phenology trend estimation | Li, Xueying, Zhu, Wenquan, Xie, Zhiying, Zhan, Pei, Huang, Xin, Sun, Lixin, Duan, Zheng | Reflectance, Anisotropy, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | |
| Assessment and comparison of six machine learning models in estimating evapotranspiration over croplands using remote sensing and meteorological factors | Liu, Yan, Zhang, Sha, Zhang, Jiahua, Tang, Lili, Bai, Yun | Reflectance, Anisotropy | |
| Can vegetation index track the interannual variation in gross primary production of temperate deciduous forests? | Liu, Fan, Wang, Chuankuan, Wang, Xingchang | Reflectance, Anisotropy | |
| 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 | |
| Validating commonly used drought indicators in Kenya | Bowell, Andrew, Salakpi, Edward E, Guigma, Kiswendsida, Muthoka, James M, Mwangi, John, Rowhani, Pedram | Land Use/Land Cover Classification, Reflectance, Anisotropy, 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 | |
| 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 | |
| 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 |