N: 90 S: -90 E: 180 W: -180
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
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 (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
USER'S GUIDE
ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)
PRODUCT QUALITY ASSESSMENT
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Predictive performance of machine learning model with varying sampling | Bouasria, Abdelkrim, Bouslihim, Yassine, Gupta, Surya, Taghizadeh-Mehrjardi, Ruhollah, Hengl, Tomislav | Reflectance, Anisotropy, Photosynthesis, Primary Production, Vegetation Productivity | |
| Multisource Maximum Predictor Discrepancy for Unsupervised Domain | Ma, Yuchi, Yang, Zhengwei, Zhang, Zhou | Reflectance, Anisotropy | |
| Modeling Global Vegetation Gross Primary Productivity, Transpiration and | Wang, Y., Braghiere, R. K., Longo, M., Norton, A. J., Kohler, P., Doughty, R., Yin, Y., Bloom, A. A., Frankenberg, C. | Reflectance, Anisotropy | |
| Observations of satellite land surface phenology indicate that maximum leaf greenness is more associated with global vegetation productivity than growing season ... | Gao, Xiaojie, McGregor, Ian R., Gray, Josh M., Friedl, Mark A., Moon, Minkyu | Reflectance, Anisotropy, Plant Phenology, Enhanced Vegetation Index (EVI) | |
| Projecting live fuel moisture content via deep learning | Miller, Lynn, Zhu, Liujun, Yebra, Marta, Rudiger, Christoph, Webb, Geoffrey I. | RADAR IMAGERY, Terrain Elevation, Topographical Relief Maps, Digital Elevation/Terrain Model (DEM), Reflectance, Anisotropy | |
| Skill and lead time of vegetation drought impact forecasts based on soil moisture observations | Li, Yizhi, van Dijk, Albert I.J.M., Tian, Siyuan, Renzullo, Luigi J. | Land Use/Land Cover Classification, Reflectance, Anisotropy | |
| Seasonal forecast of soil moisture over Mediterranean-climate forest | Chandra Joshi, Rakesh, Ryu, Dongryeol, Lane, Patrick N.J., Sheridan, Gary J. | Land Surface Temperature, Emissivity, Reflectance, Anisotropy | |
| Satellite solarinduced chlorophyll fluorescence tracks physiological drought stress development during 2020 southwest US drought | Zhang, Yao, Fang, Jianing, Smith, William Kolby, Wang, Xian, Gentine, Pierre, Scott, Russell L., Migliavacca, Mirco, Jeong, Sujong, Litvak, Marcy, Zhou, Sha | Reflectance, Anisotropy | |
| STEEP: A remotely-sensed energy balance model for evapotranspiration | Bezerra, Ulisses A., Cunha, John, Valente, Fernanda, Nobrega, Rodolfo L.B., Andrade, Joao M., Moura, Magna S.B., Verhoef, Anne, Perez-Marin, Aldrin M., Galvao, Carlos O. | Reflectance, Anisotropy, Evapotranspiration, Latent Heat Flux | |
| Utilization of synthetic minority oversampling technique for improving potato yield prediction using remote sensing data and machine learning algorithms with small ... | Ebrahimy, Hamid, Wang, Yi, Zhang, Zhou | Reflectance, Anisotropy, Land Surface Temperature, Emissivity | |
| Unravelling geological controls on groundwater flow and surface | Marti, Etienne, Leray, Sarah, Villela, Daniela, Maringue, Jose, Yanez, Gonzalo, Salazar, Esteban, Poblete, Fernando, Jimenez, Jose, Reyes, Gabriela, Poblete, Guillermo, Huaman, Zeidy, Figueroa, Ronny, Araya Vargas, Jaime, Sanhueza, Jorge, Munoz, Marjorie, Charrier, Reynaldo, Fernandez, Gabriel | Reflectance, Anisotropy | |
| A dynamic hierarchical Bayesian approach for forecasting vegetation condition | Salakpi, Edward E., Hurley, Peter D., Muthoka, James M., Bowell, Andrew, Oliver, Seb, Rowhani, Pedram | Reflectance, Anisotropy | |
| A hierarchical category structure based convolutional recurrent neural network (HCS-ConvRNN) for Land-Cover classification using dense MODIS Time-Series data | Li, Jiayi, Zhang, Ben, Huang, Xin | Land Use/Land Cover Classification, Reflectance, Anisotropy | |
| A convolutional neural network for spatial downscaling of satellite-based solar-induced chlorophyll fluorescence (SIFnet) | Gensheimer, Johannes, Turner, Alexander J., Kohler, Philipp, Frankenberg, Christian, Chen, Jia | Atmospheric Carbon Dioxide, Solar Induced Fluorescence, Reflectance, Anisotropy | |
| A Bayesian Domain Adversarial Neural Network for Corn Yield Prediction | Ma, Yuchi, Zhang, Zhou | Reflectance, Anisotropy | |
| A model framework to investigate the role of anomalous land surface processes in the amplification of summer drought across Ireland during 2018 | Ishola, Kazeem A., Mills, Gerald, Fealy, Reamonn M., Fealy, Rowan | Reflectance, Anisotropy, Land Surface Temperature, Emissivity | |
| A view from space on global flux towers by MODIS and Landsat: the FluxnetEO data set | Walther, Sophia, Besnard, Simon, Nelson, Jacob Allen, El-Madany, Tarek Sebastian, Migliavacca, Mirco, Weber, Ulrich, Carvalhais, Nuno, Ermida, Sofia Lorena, Brummer, Christian, Schrader, Frederik, Prokushkin, Anatoly Stanislavovich, Panov, Alexey Vasilevich, Jung, Martin | Land Surface Temperature, Emissivity, Reflectance, Anisotropy, Albedo | |
| An operational downscaling method of solar-induced chlorophyll fluorescence (SIF) for regional drought monitoring | Hong, Zhiming, Hu, Yijie, Cui, Changlu, Yang, Xining, Tao, Chongxin, Luo, Weiran, Zhang, Wen, Li, Linyi, Meng, Lingkui | Land Use/Land Cover Classification, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Reflectance, Anisotropy | |
| 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) | |
| An enhanced spatiotemporal fusion method Implications for DNN based time-series LAI estimation by using Sentinel-2 and MODIS | Li, Yan, Ren, Yanzhao, Gao, Wanlin, Jia, Jingdun, Tao, Sha, Liu, Xinliang | Reflectance, Anisotropy | |
| A Reconstructed Global Daily Seamless SIF Product at 0.05 Degree | Hu, Jiaochan, Jia, Jia, Ma, Yan, Liu, Liangyun, Yu, Haoyang | Reflectance, Anisotropy, Albedo | |
| A new spatialtemporal depthwise separable convolutional fusion network for generating Landsat 8-day surface reflectance time series over forest regions | Zhang, Yuzhen, Liu, Jindong, Liang, Shunlin, Li, Manyao | Reflectance, Anisotropy | |
| Biogeographic variability in wildfire severity and post-fire vegetation recovery across the European forests via remote sensing-derived spectral metrics | Nole, Angelo, Rita, Angelo, Spatola, Maria Floriana, Borghetti, Marco | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Reflectance, Anisotropy, Fire Ecology, Biomass Burning, Wildfires, Fire Occurrence, Burned Area | |
| Bayesian additive regression trees in spatial data analysis with sparse | Kim, Chanmin | Reflectance, Anisotropy, Fossil Fuel Burning, Atmospheric Carbon Dioxide | |
| Bayesian atmospheric correction over land: Sentinel-2/MSI and Landsat | Yin, Feng, Lewis, Philip E., Gomez-Dans, Jose L. | Reflectance, Anisotropy |