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Description

The MOD09GA Version 6.1 product provides an estimate of the surface spectral reflectance of Terra 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 (km) observation bands and geolocation flags. The reflectance layers from the MOD09GA are used as the source data for many of the MODIS land products.

Known Issues

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
Terra
Instruments
MODIS
Projects
TERRA
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
2000-02-24 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
C2202497474-LPCLOUD
Data State
ACTIVE
Number of Files/Granules
3055500
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/Terra Surface Reflectance Daily L2G Global 1km and 500m SIN Grid V061 [Dataset]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/MODIS/MOD09GA.061 Date Accessed: 2026-08-02

File Naming Convention

MOD09GA.A2025219.h05v10.061.2025221031815.hdf

The file name begins with the Product Short Name (MOD09GA) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2025219), the Tile Identifier which is horizontal tile and vertical tile provided as hXXvYY (h05v10), the Version of the data collection (061), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2025221031815), 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 Topic
An End-to-End Foundation Model-Based Framework for Robust LAI Retrieval Gu, Xiangfeng, Li, Wenyuan, Guan, Shikang Reflectance
A harmonized 20002024 dataset of daily river ice concentration and annual phenology for major Arctic rivers Qiu, Jiahui, Luojus, Kari, Kaartinen, Harri, Qiu, Yubao, Silander, Jari, Patro, Epari Ritesh, Klove, Bjorn, Haghighi, Ali Torabi Reflectance
A Costefficient and robust approach to monitor ecosystem photosynthesis using nearinfrared enabled cameras Syahid, Luri Nurlaila, Luo, Xiangzhong, Zhao, Ruiying, Yu, Liyao, Tan, Li Ming, Detto, Matteo, Sonnentag, Oliver Reflectance, Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Vegetation Cover, Plant Phenology, Plant Characteristics
Identifying predictors of tropical cyclone impacts on coastal agriculture to assess coastal wetland buffering signals Rowland, Phebe I., Wartman, Melissa, Nuyts, Siegmund, Duarte de Paula Costa, Micheli Reflectance
Automated Machine Learning for High-Resolution Daily and Hourly Methane Emission Mapping for Rice Paddies over South Korea: Integrating MODIS, ERA5-Land, and Soil Data Jang, Jiah, Kim, Seung Hee, Kafatos, Menas, Cho, Jaeil, Yoo, Gayoung, Jeong, Sujong, Lee, Yangwon Reflectance
Combined effects of site and model parameterization for soil respiration components in a Canadian wildfire chronosequence Zobitz, John, Zhou, Xuan, Aaltonen, Heidi, Koster, Egle, Berninger, Frank, Pumpanen, Jukka, Koster, Kajar Photosynthesis, Primary Production, Vegetation Productivity, Reflectance, Land Surface Temperature, Emissivity
Comparative machine learning and deep learning approaches for Azizi, Mahan, Abbasi, Ali, Asli Charandabi, Mohammad Reza Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Surface Pressure, Heat Flux, Longwave Radiation, Shortwave Radiation, Air Temperature, Specific Humidity, Evapotranspiration, Wind Speed, Soil Moisture/Water Content, Soil Temperature, Land Surface Temperature, Snow Cover, Snow Depth, Snow Water Equivalent, Runoff, Reflectance, Emissivity
Comparison of Sentinel-2 and MODIS for estimating GPP along an ecosystem gradient in eastern Germany Sayeed, Mostafa, Ahmadpour, Somayeh, Trachte, Katja Reflectance, Albedo, Anisotropy, Land Surface Temperature, Emissivity
Multi-Sensor Spatiotemporal Fusion for 30-m Daily Gapless Snow Cover Wu, Jinhang, Zhang, Xueliang, Xiao, Pengfeng, Jia, Yumeng, Tang, Bo, Liu, Yan Reflectance, Terrain Elevation, RADAR IMAGERY, Topographical Relief Maps, Albedo, Snow Cover
Runoff from Greenland's firn areawhy do MODIS, RCMs and a firn model disagree? Machguth, Horst, Tedstone, Andrew, Kuipers Munneke, Peter, Brils, Max, Noel, Brice, Clerx, Nicole, Jullien, Nicolas, Fettweis, Xavier, van den Broeke, Michiel Ice Velocity, Reflectance, Albedo, Snow Cover
The Accuracy, Spatial Consistency, and Impact Factors of Global Cropland Products in Karst Landscapes: A Case Study of the YunnanGuizhou Plateau Xia, Yi, Bao, Li, Xia, Yunsheng, Liu, Guangjie Terrain Elevation, RADAR IMAGERY, Topographical Relief Maps, Reflectance
Vegetation Water Stress Response-Driven Approach for Verifying Vegetation Drought Monitoring Results: A Case Study of the Yangtze River Basin, China Wu, Lixin, Zhang, Zhimei, Haseeb, Muhammad, Jiao, Zhijun Land Use/Land Cover Classification, Reflectance
How well does MODIS GPP capture alpine productivity of a Tibetan Pillai, Nithin D, Wille, Christian, Helbig, Manuel, Sachs, Torsten Photosynthesis, Primary Production, Vegetation Productivity, Reflectance
An Evaluation of Machine Learning Methods for Leaf Area Index Retrieval Wang, Dong, Miao, Lijuan, Lu, Yutian, Jiang, Hanyang, Liu, Qiang Reflectance
Can the MODIS EVI formula be directly applied to other sensor data? A case study with Landsat data Bai, Yafen, Xu, Hanqiu, Su, Guifen, Shi, Tingting, Yang, Lijuan Reflectance
Divergent mechanisms regulating freezing rain-induced spring phenology Zhang, Yating, Chen, Jinghua, Wang, Shaoqiang, Wang, Miaomiao, Zhao, Ziqi, Zhou, Zehan, Deng, Zhuoying, Peng, Haoyu, Ma, Jiageng, Wang, Xueqing, Xiao, Yuhan Land Use/Land Cover Classification, 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
Amazon forest nutrient limitation is mitigated by distant fire emissions Descals, Adria, Janssens, Ivan A., Penuelas, Josep Solar Induced Fluorescence, Chlorophyll, Primary Production, Leaf Characteristics, Reflectance, Fire Ecology, Biomass Burning, Wildfires, Fire Occurrence, Burned Area, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar)
Ice-resistant breakwater rock sizing at Elim, Alaska Engel, Chandler, Morriss, Blaine Reflectance
Monitoring Flood Inundation Dynamics From Space Campo, C., Tamagnone, P., Choy, S., Tran, T. D., Schumann, G. J.P., Kuleshov, Y. Atmospheric Water Vapor, Precipitation, Brightness Temperature, Surface Soil Moisture, Terrain Elevation, Vegetation Height, Reflectance, Reflectance
PIXAL: a physics-inspired explainable machine learning architecture for Greenland ice albedo modeling Antwerpen, Raf, Tedesco, Marco, Gentine, Pierre, van de Berg, Willem Jan, Fettweis, Xavier Reflectance, Albedo, Snow Cover
The role of the onset of spring vegetation greening in moisture recycling process of the Eastern Tibetan Plateau Hou, Miao, Yurova, Alla Atmospheric Water Vapor, Precipitation, Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Leaf Area Index (LAI), Reflectance
The shrinking Caspian Sea: Ecohydrological responses to human and climate pressures Duku, Jesse, Tourian, Mohammad J., Azarderakhsh, Marzi, Abbasov, Rovshan, Mehran, Ali, Haghighi, Ali Torabi, Xenarios, Stefanos, Boschee, Azara, Babagiray, Salih, Sadegh, Mojtaba, Shokri, Nima, Nazemi, Ali, Farahmand, Alireza, Ashraf, Samaneh, Khujanazarov, Temur, Hassanzadeh, Elmira, Najib, Dalal, Placht, Daniel, Mashtayeva, Shamshagul, Rets, Ekaterina, Norouzi, Hamid, Madani, Kaveh, Shirzaei, Manoochehr, ShafizadehMoghadam, Hossein, Miao, Chiyuan, Mirchi, Ali, Wang, Shuo, AghaKouchak, Amir Reflectance
Geo-OLM: Enabling Sustainable Earth Observation Studies with Stamoulis, Dimitrios, Marculescu, Diana Reflectance, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Aerosol Optical Depth/Thickness, Land Surface Temperature, Emissivity
MULTI-AGENT GEOSPATIAL COPILOTS FOR REMOTE SENSING WORKFLOWS Lee, Chaehong, Paramanayakam, Varatheepan, Karatzas, Andreas, Jian, Yanan, Fore, Michael, Liao, Heming, Yu, Fuxun, Li, Ruopu, Anagnostopoulos, Iraklis, Stamoulis, Dimitrios Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Aerosol Optical Depth/Thickness, Land Surface Temperature, Emissivity, 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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