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Description

The MYD09GA Version 6.1 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 kilometer 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

  • Prior to the Aqua MODIS launch, Band 6 exhibited several anomalous detectors. Band 6 performance degraded seriously after launch and presently a majority of the Band 6 detectors are non-functional. Science users should read and use the non-functional detector flags and decide for themselves the optimum manner to handle non-functional detector "gaps" for their products. For complete information please refer to the MODIS Characterization Support Team (MCST) website.
  • 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 6.1 surface reflectance data products: (1) Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 – 2017, and (2) A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).

Product Summary

Platforms
Aqua
Instruments
MODIS
Spatial Extent

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

Spatial Resolution
500 Meters x 500 Meters
1000 Meters x 1000 Meters
Spatial Reference System(s)
MODIS Sinusoidal Tiling System
Location
GLOBAL
Coordinate System
CARTESIAN
Granule Spatial Representation
GEODETIC
Temporal Extent
2002-07-04 to Present
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
C2202498116-LPCLOUD
Data State
ACTIVE
Number of Files/Granules
2746706
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. (2021). MODIS/Aqua Surface Reflectance Daily L2G Global 1km and 500m SIN Grid V061 [Data set]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/MODIS/MYD09GA.061 Date Accessed: 2026-02-13

File Naming Convention

MYD09GA.A2025222.h00v09.061.2025224032058.hdf

The file name begins with the Product Short Name (MYD09GA) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2025222), the Tile Identifier which is horizontal tile and vertical tile provided as hXXvYY (h10v10), the Version of the data collection (061), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2025224032058), and the Data Format (hdf).

Documents

USER'S GUIDE

ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)

PRODUCT QUALITY ASSESSMENT

SCIENCE DATA PRODUCT VALIDATION

GENERAL DOCUMENTATION

Publications Citing This Dataset

Filters
Title Year Author
Evaluation of satellite-derived estimates of lake ice cover timing on Linnevatnet, Kapp Linne, Svalbard using in-situ data Tuttle, S. E.
How long did crops survive from floods caused by Cyclone Idai in Mozambique detected with multi-satellite data Bofana, J.
Long-term series of chlorophyll-a concentration in Brazilian semiarid lakes from MODIS imagery Ventura, D. L. T.
Saharan dust and childhood respiratory symptoms in Benin McElroy, S.
Adaptability of MODIS daily cloud-free snow cover 500 m dataset over China in Hutubi River Basin based on snowmelt runoff model Meng, X. Y.
Climate-driven variations in suspended particulate matter dominate water clarity in shallow lakes Fang, C.
Assessing the inter-annual variability of vegetation phenological events observed from satellite vegetation index time series in dryland sites Kato, A.
Relationship between tir and nir-swir as indicator of vegetation water availability Holzman, M. E.
Changes in the greenness of mountain pine (Pinus mugo Turra) in the subalpine zone related to the winter climate Lukasova, V.
Spatial-temporal distribution of the freeze–thaw cycle of the largest lake (Qinghai lake) in china based on machine learning and modis from 2000 to 2020 Han, W.
SHOWING 10 OF 45

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
gflags_1 Geolocation flags Bit Field uint8 255 0 to 248 N/A
granule_pnt _1 Granule pointer N/A uint8 255 0 to 254 N/A
iobs_res_1 Observation number N/A uint8 255 0 to 254 N/A
num_observations_1km Number of observations within a  pixel N/A int8 -1 0 to 127 N/A
num_observations_500m Number of observations per 500m pixel N/A int8 -1 0 to 127 N/A
obscov_500m_1 Observation coverage Percent int8 -1 0 to 100 0.01
orbit_pnt_1 Orbit pointer N/A int8 -1 0 to 15 N/A
QC_500m_1 Surface Reflectance 500m Quality Assurance Bit Field uint32 787410671 0 to 4294966019 N/A
q_scan_1 250m scan value information N/A uint8 255 0 to 254 N/A
Range_1 Distance to sensor Meters uint16 0 27000 to 65535 25
SensorAzimuth_1 Azimuth angle to sensor Degree int16 -32767 -18000 to 18000 0.01
SensorZenith_1 Zenith angle to sensor Degree int16 -32767 0 to 18000 0.01
SolarAzimuth_1 Azimuth angle to sun Degree int16 -32767 -18000 to 18000 0.01
SolarZenith_1 Zenith angle to sun Degree int16 -32767 0 to 18000 0.01
state_1km_1 1km Reflectance Data State QA Bit Field uint16 65535 0 to 57335 N/A
sur_refl_b01_1 Surface Reflectance Band 1 N/A int16 -28672 -100 to 16000 0.0001
sur_refl_b02_1 Surface Reflectance Band 2 N/A int16 -28672 -100 to 16000 0.0001
sur_refl_b03_1 Surface Reflectance Band 3 N/A int16 -28672 -100 to 16000 0.0001
sur_refl_b04_1 Surface Reflectance Band 4 N/A int16 -28672 -100 to 16000 0.0001
sur_refl_b05_1 Surface Reflectance Band 5 N/A int16 -28672 -100 to 16000 0.0001
sur_refl_b06_1 Surface Reflectance Band 6 N/A int16 -28672 -100 to 16000 0.0001
sur_refl_b07_1 Surface Reflectance Band 7 N/A int16 -28672 -100 to 16000 0.0001
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