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Description

The MYD09GA Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the MYD09GA Version 6.1 data product.

The MYD09GA Version 6 product provides an estimate of the surface spectral reflectance of Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Bands 1 through 7, corrected for atmospheric conditions such as gasses, aerosols, and Rayleigh scattering. Provided along with the 500 meter (m) surface reflectance, observation, and quality bands are a set of ten 1 km observation bands and geolocation flags. The reflectance layers from the MYD09GA are used as the source data for many of the MODIS land products.

Known Issues

  • The Collection 6 MODIS Land Surface Reflectance product (MYD09) may incorrectly flag retrievals as ‘High Aerosol’ over brighter surfaces and at higher view angles. This will impact the downstream MODIS BRDF/Albedo (MCD43) and Vegetation Index (MOD13 and MYD13) data products which use the aerosol quantity flag to screen out high aerosol values.
  • Corrections were implemented in Collection 6.1 reprocessing.
  • For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.

Version Description

The following changes and improvements were implemented for inputs to MODIS Version 6 surface reflectance data products: (1) Improvements to the aerosol retrieval and correction algorithm along with new aerosol retrieval look-up tables, (2) Refinements to the internal snow, cloud, and cloud shadow detection algorithms. Uses Bidirectional Reflectance Distribution Function (BRDF) database to better constrain the different threshold used, (3) Processes ocean bands to create a new Surface Reflectance Ocean product and provides Quality Assurance (QA) datasets for these bands, and (4) Improved discrimination of salt pans from cloud and snow, along with the inclusion of a salt pan flag in the QA band.

Product Summary

Platforms
AQUA
Instruments
MODIS
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
2002-07-04 to 2023-02-26
Temporal Resolution
1 Day
Data Partner
Land Processes Distributed Active Archive Center (LP DAAC) ,
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
C2763370201-LPCLOUD
Data State
DEPRECATED
Number of Files/Granules
0
Processing Level
2G
Published
Updated
Science Keywords
Reflectance

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

Vermote, E., & Wolfe, R. (2015). MYD09GA MODIS/Aqua Surface Reflectance Daily L2G Global 1kmand 500m SIN Grid V006 [Data set]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/MODIS/MYD09GA.006 Date Accessed: 2026-05-18

File Naming Convention

MYD09GA.A2002281.h03v07.006.2015151091940.hdf

The file name begins with the Product Short Name (MYD09GA) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2002281), the Tile Identifier which is horizontal tile and vertical tile provided as hXXvYY (h03v07), the Version of the data collection (006), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2015151091940), and the Data Format (hdf).

Documents

Publications Citing This Dataset

Filters
Title Year Author Topic
Disentangling the effects of orographic forcing and soil moisture on shallow cumulus in a semi-arid grassland Guo, Yali, Chen, Jingyi, Shi, Hongrong, Chen, Hongbin, Lu, Chunsong Reflectance
Estimating the Near-Surface Air Temperature Field Using Satellite-Based Remote Sensing of Land Surface Temperatures Frat Ors, Pelin, Mahdavi, Ardeshir Albedo, Anisotropy, Land Surface Temperature, Emissivity, Reflectance
A dataset of daily cloud-free remote sensing indices for the cryosphere in High Mountain Asia (20002023) SUN, Xingliang, SHI, Kaidan, HU, Zhimin, FENG, Min, GUO, Xuejun Reflectance
Differential effects of environmental predictability on ungulate Standen, Madeline P., Ditmer, Mark A., Stoner, David C., Hersey, Kent R., Carter, Neil H. Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Reflectance
Enhanced structural diversity increases European forest resilience and potentially compensates for climate-driven declines Pickering, Mark, Elia, Agata, Oton, Gonzalo, Piccardo, Matteo, Ceccherini, Guido, Forzieri, Giovanni, Migliavacca, Mirco, Cescatti, Alessandro, Girardello, Marco RADAR IMAGERY, Terrain Elevation, Topographical Relief Maps, Digital Elevation/Terrain Model (DEM), Reflectance, Plant Phenology, Enhanced Vegetation Index (EVI)
Multiple Impacts of Climate Change and Anthropogenic Activities on Xie, Ge, Zhang, Yibo, Wang, Qing, Shi, Kun, Zhang, Yunlin, Zhou, Yongqiang, Qin, Boqiang, He, Junliang, Li, Na Reflectance
Increasing global human exposure to wildland fires despite declining burned area Teymoor Seydi, Seyd, Abatzoglou, John T., Jones, Matthew W., Kolden, Crystal A., Filippelli, Gabriel, Hurteau, Matthew D., AghaKouchak, Amir, Luce, Charles H., Miao, Chiyuan, Sadegh, Mojtaba Land Use/Land Cover Classification, Reflectance
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
Retrieval of Snow Grain Size over the Tibetan Plateau: Preliminary Zhang, Yunlong, Tian, Yixiang Reflectance, Reflectance, Terrain Elevation
Estimation of Vegetation Parameters of the VIC Model Using Remotely Sensed Data Gomez, Edna Lucia Espinosa, Rodriguez, Leticia, Zimmermann, Erik Albedo, Anisotropy, Reflectance, Aerosol Backscatter, Aerosol Extinction, Aerosol Optical Depth/Thickness, Angstrom Exponent, Aerosol Particle Properties, Aerosol Radiance, Carbonaceous Aerosols, Cloud Condensation Nuclei, Dust/Ash/Smoke, Nitrate Particles, Organic Particles, Particulate Matter, Sulfate Particles, Trace Gases/Trace Species, Atmospheric Emitted Radiation, Emissivity, Optical Depth/Thickness, Radiative Flux, Reflectance, Transmittance, Atmospheric Stability, Humidity, Total Precipitable Water, Water Vapor Profiles, Cloud Condensation Nuclei, Cloud Droplet Concentration/Size, Cloud Liquid Water/Ice, Cloud Optical Depth/Thickness, Cloud Asymmetry, Cloud Ceiling, Cloud Frequency, Cloud Height, Cloud Top Pressure, Cloud Top Temperature, Cloud Vertical Distribution, Cloud Emissivity, Cloud Radiative Forcing, Cloud Reflectance, Rain Storms, Atmospheric Ozone, Surface Pressure, Heat Flux, Longwave Radiation, Shortwave Radiation, Surface Temperature, Evapotranspiration, Surface Winds, Rain, Precipitation Rate, Snow, Soil Moisture/Water Content, Soil Temperature, Land Surface Temperature, Snow Water Equivalent, Runoff, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar)
Distinguishing the Impacts and Gradient Effects of Climate Change and Lv, WenBo, Liu, FangMei, Cai, Kai, Cao, Yue, Deng, MengLing, Liang, Wei, Yan, JianWu, Wang, GuangYu Land Use/Land Cover Classification, Reflectance
Estimating the daily mean blue-sky land surface albedo on the Tibetan Plateau using convolutional neural network Ma, Bin, Ma, Yaoming, Ma, Weiqiang, Xie, Zhipeng, Han, Cunbo, Wang, Binbin Albedo, Anisotropy, Snow Cover, Aerosol Optical Depth/Thickness, Reflectance
Airfall volume of the 15 January 2022 eruption of Hunga volcano estimated from ocean color changes Kelly, Liam J., Fauria, Kristen E., Manga, Michael, Cronin, Shane J., Latuila, Folauhola Helina, Paredes-Marino, Joali, Mittal, Tushar, Bennartz, Ralf Reflectance
Modeling the hotspot effect for vegetation canopies based on path length distribution Li, Weihua, Yan, Guangjian, Mu, Xihan, Tong, Yiyi, Zhou, Kun, Xie, Donghui Topography, Canopy Characteristics, Digital Elevation/Terrain Model (DEM), Lidar, LIDAR WAVEFORM, Reflectance
Using CYGNSS and L-band Radiometer Observations to Retrieve Surface Water Fraction: A Case Study of the Catastrophic Flood of 2022 in Pakistan Ma, Zhongmin, Zhang, Shuangcheng, Liu, Qi, Feng, Yanming, Guo, Qinyu, Zhao, Hebin, Feng, Yuxuan Total Surface Precipitation Rate, Reflectance, Radar Cross-Section, Radar Reflectivity, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Three-dimensional copula framework for early warning of agricultural Afshar, Mehdi H., Sorman, Ali Unal, Tosunoglu, Fatih Reflectance
Evaluating gross primary productivity over 9 ChinaFlux sites based on random forest regression models, remote sensing, and eddy covariance data Chang, Xiaoqing, Xing, Yanqiu, Gong, Weishu, Yang, Cheng, Guo, Zhen, Wang, Dejun, Wang, Jiaqi, Yang, Hong, Xue, Gang, Yang, Shuhang Reflectance
Estimating Early Summer Snow Depth on Sea Ice Using a Radiative Transfer Wang, Mingfeng, Oppelt, Natascha Reflectance
Geo-Intelligent Retrieval Framework Based on Machine Learning in the Cloud Environment: A Case Study of Soil Moisture Retrieval Li, Zhenghao, Yuan, Qiangqiang, Zhang, Liangpei Land Surface Temperature, Emissivity, Reflectance, Albedo, Anisotropy
Burned area and carbon emissions across northwestern boreal North America from 20012019 Potter, Stefano, Cooperdock, Sol, Veraverbeke, Sander, Walker, Xanthe, Mack, Michelle C., Goetz, Scott J., Baltzer, Jennifer, Bourgeau-Chavez, Laura, Burrell, Arden, Dieleman, Catherine, French, Nancy, Hantson, Stijn, Hoy, Elizabeth E., Jenkins, Liza, Johnstone, Jill F., Kane, Evan S., Natali, Susan M., Randerson, James T., Turetsky, Merritt R., Whitman, Ellen, Wiggins, Elizabeth, Rogers, Brendan M. Reflectance, Land Use/Land Cover Classification, Fire Occurrence, Forest Fire Science, Burned Area, Aquatic Ecosystems, Terrestrial Ecosystems, Vegetation, Soils, Vegetation Cover, Forests, Biomass Burning, Surface Temperature, Precipitation Amount, Fire Dynamics, Carbon, Biomass, Soil Moisture/Water Content, Topographic Effects, Emissions, Carbon
Assessment of water demands for irrigation using energy balance and satellite data fusion models in cloud computing: A study in the Brazilian semiarid region Ferreira, Thomas R., Maguire, Mitchell S., da Silva, Bernardo B., Neale, Christopher M.U., Serrao, Edivaldo A.O., Ferreira, Jessica D., de Moura, Magna S.B., dos Santos, Carlos A.C., Silva, Madson T., Rodrigues, Lineu N., Carvalho, Herica F.S. Albedo, Anisotropy, Reflectance, Land Surface Temperature, Emissivity
Comparing forest and grassland drought responses inferred from eddy covariance and Earth observation Hoek van Dijke, Anne J., Orth, Rene, Teuling, Adriaan J., Herold, Martin, Schlerf, Martin, Migliavacca, Mirco, Machwitz, Miriam, van Hateren, Theresa C., Yu, Xin, Mallick, Kaniska Land Surface Temperature, Emissivity, Reflectance
Phenophase-based comparison of field observations to satellite-based actual evaporation estimates of a natural woodland: miombo woodland, southern ... Zimba, Henry, Coenders-Gerrits, Miriam, Banda, Kawawa, Schilperoort, Bart, van de Giesen, Nick, Nyambe, Imasiku, Savenije, Hubert H. G. Land Use/Land Cover Classification, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Plant Phenology, Enhanced Vegetation Index (EVI), Reflectance
Development and validation of a new MODIS snow-cover-extent product over China Hao, Xiaohua, Huang, Guanghui, Zheng, Zhaojun, Sun, Xingliang, Ji, Wenzheng, Zhao, Hongyu, Wang, Jian, Li, Hongyi, Wang, Xiaoyan Land Use/Land Cover Classification, Reflectance
Evaluation of Satellite-Derived Estimates of Lake Ice Cover Timing on Tuttle, Samuel E., Roof, Steven R., Retelle, Michael J., Werner, Alan, Gunn, Grant E., Bunting, Erin L. Reflectance
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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 Description Units Data Type Fill Value Valid Range Scale Factor Offset
gflags_1 Geolocation flags Bit Field uint8 255 0 to 248 N/A N/A
granule_pnt _1 Granule pointer N/A uint8 255 0 to 254 N/A N/A
iobs_res_1 Observation number N/A uint8 255 0 to 254 N/A N/A
num_observations_1km Number of observations within a  pixel N/A int8 -1 0 to 127 N/A N/A
num_observations_500m Number of observations per 500m pixel N/A int8 -1 0 to 127 N/A N/A
obscov_500m_1 Observation coverage Percent int8 -1 0 to 100 0.01 N/A
orbit_pnt_1 Orbit pointer N/A int8 -1 0 to 15 N/A N/A
QC_500m_1 Surface Reflectance 500m Quality Assurance Bit Field uint32 787410671 0 to 4294966019 N/A N/A
q_scan_1 250m scan value information N/A uint8 255 0 to 254 N/A N/A
Range_1 Distance to sensor Meters uint16 0 27000 to 65535 25 N/A
SensorAzimuth_1 Azimuth angle to sensor Degree int16 -32767 -18000 to 18000 0.01 N/A
SensorZenith_1 Zenith angle to sensor Degree int16 -32767 0 to 18000 0.01 N/A
SolarAzimuth_1 Azimuth angle to sun Degree int16 -32767 -18000 to 18000 0.01 N/A
SolarZenith_1 Zenith angle to sun Degree int16 -32767 0 to 18000 0.01 N/A
state_1km_1 1km Reflectance Data State QA Bit Field uint16 65535 0 to 57335 N/A N/A
sur_refl_b01_1 Surface Reflectance Band 1 N/A int16 -28672 -100 to 16000 0.0001 N/A
sur_refl_b02_1 Surface Reflectance Band 2 N/A int16 -28672 -100 to 16000 0.0001 N/A
sur_refl_b03_1 Surface Reflectance Band 3 N/A int16 -28672 -100 to 16000 0.0001 N/A
sur_refl_b04_1 Surface Reflectance Band 4 N/A int16 -28672 -100 to 16000 0.0001 N/A
sur_refl_b05_1 Surface Reflectance Band 5 N/A int16 -28672 -100 to 16000 0.0001 N/A
sur_refl_b06_1 Surface Reflectance Band 6 N/A int16 -28672 -100 to 16000 0.0001 N/A
sur_refl_b07_1 Surface Reflectance Band 7 N/A int16 -28672 -100 to 16000 0.0001 N/A
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