Landsat Collection 2 Surface Reflectance

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Surface reflectance improves comparison between multiple images over the same region by accounting for atmospheric effects such as aerosol

 scattering and thin clouds, which can help in the detection and characterization of Earth surface change. Surface reflectance is generated from Level-1 inputs that meet the <76 degrees Solar Zenith Angle constraint and include the required auxiliary data inputs to generate a scientifically viable product.

Please note that Level-2 Multispectral Scanner (MSS) surface reflectance products will only become available upon the maturity of an operational atmospheric compensation algorithm which satisfies the USGS Landsat program requirements.

Landsat 8-9 Operational Land Imager (OLI)

Landsat 8-9 OLI Collection 2 Surface Reflectance data are generated using the Land Surface Reflectance Code (LaSRC) (version 1.5.0), which makes use of the coastal aerosol band to perform aerosol inversion tests, uses auxiliary climate data from MODIS, and a unique radiative transfer model (Vermote et al., 2016).

LaSRC hardcodes the view zenith angle to “0”, and the solar zenith and view zenith angles are used for calculations as part of the atmospheric correction. 

The Land Surface Reflectance Code (LaSRC) Product Guide contains details about the LaSRC algorithm and the Surface Reflectance data products created from it. 

Landsat 4-5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+)

Landsat 4-5 TM and Landsat 7 ETM+ Collection 2 Surface Reflectance are generated using the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) algorithm (version 3.4.0), a specialized software originally developed through a National Aeronautics and Space Administration (NASA) Making Earth System Data Records for Use in Research Environments (MEaSUREs) grant by NASA Goddard Space Flight Center (GSFC) and the University of Maryland (Masek et al., 2006).

The software applies Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric correction routines to Level-1 data products. Water vapor, ozone, atmospheric height, aerosol optical thickness, and digital elevation are input with Landsat data to the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) radiative transfer models to generate top of atmosphere (TOA) reflectance, surface reflectance, TOA brightness temperature, and masks for clouds, cloud shadows, adjacent clouds, land, and water.

The Landsat 4-7 Surface Reflectance Product Guide contains details about the LEDAPS algorithm and the Surface Reflectance data products created from it. 

Differences in Surface Reflectance Processing Algorithms

While both the LEDAPS and LaSRC algorithms produce similar SR products, the inputs and methods to do so differ between them.  The table below displays each algorithm.   

6S Second Simulation of a Satellite Signal in the Solar Spectrum, AOT Aerosol Optical Thickness, CFmask C Version of Function Of Mask, CMA Climate Modeling Grid - Aerosol, CMG Climate Modeling Grid, CMGDEM Climate Modeling Grid Digital Elevation Model, DDV Dark Dense Vegetation, DEM Digital Elevation Model, ETM+ Enhanced Thematic Mapper Plus, ETOPO5 Earth Topography Five Minute Grid, GSFC Goddard Space Flight Center, INT Integer, MEaSUREs Making Earth Science Data Records for Use in Research Environments, MODIS Moderate Resolution Imaging Spectroradiometer, N/A Not Applicable, NASA National Aeronautics and Space Administration, NCEP National Centers for Environmental Prediction, OLI Operational Land Imager, OMI Ozone Monitoring Instrument, QA Quality Assessment, SR Surface Reflectance, TIRS Thermal Infrared Sensor, TM Thematic Mapper, TOA Top of Atmosphere Reflectance, TOMS Total Ozone Mapping Spectrometer, XML Extensible Markup Language

Atmospheric Auxiliary Data

Collection 2 surface reflectance products require atmospheric auxiliary data input from external USGS data sources. USGS retrieves data from the data source and extracts parameters specific to Landsat Collection 2 Level-2 processing. These subset data sets are available for download for users who wish to perform Level-2 processing. It is not necessary for users to download atmospheric auxiliary data to use the Collection 2 Level-2 products.

Visit the Landsat Collection 2 Atmospheric Auxiliary web page for additional information.

Constraints and Caveats 

Most day-lit (descending) Collection 2 Landsat 4-9 scenes in the USGS archive can be processed to Surface Reflectance. However, please note the following constraints and caveats:

1. Newly acquired Landsat 7 and Landsat 8-9 Surface Reflectance products are typically available within 24 hours after a scene has been processed into Tier 1 or Tier 2. Data from all sensors utilize NASA's Goddard Earth Observing System Model Version 5 Forward Processing for Instrument Teams (GOES-5 FP-IT) Atmospheric Assimilation Products for Level-2 product generation. Visit the Landsat Collection 2 Generation Timeline for a visual look at this timeframe.

   1. Due to missing auxiliary input data and/or necessary thermal data, Surface Reflectance processing cannot be applied to data acquired during the dates listed below. 

      Sensor	Dates (DOY)	Reason
      Landsat 7	2016: May 30 (151) to Jun 12 (164) 2017: Mar 12 (071) -Mar 17 (076) 2020: Oct 5 (279) 2023: Dec 3 (337)	Missing auxiliary input data Missing auxiliary input data No data collected - Paths 35, 51, 99, 188, 204, 220 ​​​​​​​Missing auxiliary input data
      Landsat 8	2019: Dec 20 (354) - Dec 21 (355) 2020: Nov 1 (306) - Nov 3 (308) 2020: Nov 4 (309) - Nov 8 (313) 2020: Nov 9 (314) 2020: Nov 12 (317) - Nov 13 (318) 2020: Nov 14 (319) 2021: Sept 23 (266) - Sept 24 (267)	No thermal data; satellite safehold No thermal data; satellite safehold No thermal data No thermal data - paths 105, 121, 137, 153, 169, 185 No thermal data; satellite safehold No thermal data - paths 108, 124 Missing auxiliary input data

2. Landsat 8-9 OLI Band 8 and Landsat 7 ETM+ Band 8 (panchromatic band) are not processed to Top of Atmosphere or Surface Reflectance
3. Landsat 8-9 OLI Band 9 (cirrus band) is not processed to Top of Atmosphere or Surface Reflectance
4. SR is not run on scenes with a solar zenith angle of greater than 76º. The primary physical issues with retrieving SR from high solar zenith angles (low sun angle) include:
   • Solar elevation varies more near the poles [1], especially when relying upon sun-synchronous observations.
   • Lower solar elevations at high latitudes results in longer atmospheric paths (i.e., more scattering) [1].
   • The degree of uncertainty in SR retrieval greatly increases, from being negligible to highly inaccurate, at solar zenith angle > 76 degrees.
5. For reasons mentioned in #4 above, the Surface Reflectance data processed over high latitudes (> 65º) have larger uncertainty and should be analyzed carefully.
6. Corrections from OLI Bands 1 and 2 (coastal aerosol and blue bands, respectively) should not be used for analysis, as they are already used within the algorithm to perform aerosol inversion tests, making them potentially unreliable.
7. Users are cautioned against using pixels flagged as high aerosol content.
8. Aerosol retrieval is attempted over all pixels, although a separate routine is used for pixels flagged by LaSRC as water. These conditions are detailed in the Aerosol QA band
9. There are additional adverse conditions that can affect the efficacy of Landsat 8 SR retrievals, such as:
   • Hyper-arid or snow-covered regions
   • Low sun angle conditions
   • Coastal regions where land area is small relative to adjacent water
   • Areas with extensive cloud contamination
10. The cloud and cloud shadow indicators in the Surface Reflectance data product are known to report erroneous conditions in areas where temperature differentials are either too large or too small. For example, a warm cloud over extremely cold ground may not calculate enough difference in temperature to identify the cloud. Conversely, residual ice surrounded by unusually warm ground can potentially be identified as cloud.

Landsat Collection 2 Known Issues

The Landsat Collection 2 Known Issues page provides information about artifacts found in Landsat Collection 2 data products and attempts to make recommendations on how users can make corrections. 

Data Availability

Scene-based Landsat surface reflectance data are available globally for the following instruments:

• Landsat 9 Operational Land Imager 2 (OLI-2): October 2021 to present
• Landsat 8 Operational Land Imager (OLI): April 2013 to present
• Landsat 7 Enhanced Thematic Mapper Plus (ETM+): July 1999 to April 2022
• Landsat 5 Thematic Mapper (TM): March 1984 to May 2012
• Landsat 4 Thematic Mapper (TM): August 1982 to December 1993

Data Access

Landsat Collection 2 Level-2 data are available from EarthExplorer and the LandsatLook Viewer. The USGS Landsat no-cost open data policy remains intact since its inception in 2008.

New for Collection 2 is the ability for users to select individual Landsat bands for download. The EarthExplorer Bulk Download option also supports individual band selection and will add all files to the Bulk Order for download using the Bulk Download Application (BDA).

Visit the Landsat Data Access web page for information about bulk download options.  

Data Tools

Data manipulation tools that function with Moderate Resolution Imaging Spectroradiometer (MODIS) Land products are likely to work with Landsat surface reflectance data products as well. The public domain tools listed below are suggested for format conversion, science data set extraction, bit extraction (for top of atmosphere reflectance, saturation values only), and reprojection.

HDF-EOS To GeoTIFF Conversion Tool (HEG): Allows a user to reformat, re-project and perform stitching/mosaicing and subsetting operations on HDF-EOS objects. It can also reformats and re-project some SMAP, VIIRS and SRTM products. The output GeoTIFF file is ingestible into commonly used GIS applications. HEG will also write to HDF-EOS Grid & SWATH formats (i.e for Subsetting purposes) and native (or raw) binary. 

Landsat Quality Assessment (QA) Tools: Developed by the MODIS land quality assessment group to work specifically with Landsat Surface Reflectance data.

Documentation

• Landsat Cloud Optimized GeoTIFF (COG) Data Format Control Book

Landsat 8-9

• Landsat 8-9 OLI/TIRS Collection 2 Level-2 Science Product Guide 
• Landsat 8-9 OLI/TIRS Collection 2 Level- 2 Data Format Control Book
• Landsat 8-9 OLI/TIRS Calibration / Validation Algorithm Description Document 
• Landsat 8-9 OLI Level-2 Science Products Digital Object Identifier (DOI): 10.5066/P9OGBGM6

Landsat 4-7

• Landsat 4-7 Collection 2 Level-2 Science Product Guide
• Landsat 4-5 TM Collection 2 Level- 2 Data Format Control Book
• Landsat 7 ETM+ Collection 2 Level- 2 Data Format Control Book
• Landsat 4-7 LEDAPS Calibration / Validation Algorithm Description Document
• Landsat 4-5 TM Level-2 Science Products Digital Object Identifier (DOI): 10.5066/P9IAXOVV
• Landsat 7 ETM+ Level-2 Science Products Digital Object Identifier (DOI): 10.5066/P9C7I13B

Citation Information

There are no restrictions on the use of Landsat Science Products. It is not a requirement of data use, but the following citation may be used in publication or presentation materials to acknowledge the USGS as a data source and to credit the original research: 

Landsat Collection 2 Level- 2 Surface Reflectance Science Product courtesy of the U.S. Geological Survey.

The appropriate Digital Object Identifiers (DOIs) may also be included in the citation: 
Landsat 8-9 Level-2: https://doi.org/10.5066/P9OGBGM6
Landsat 7 Level-2:  https://doi.org/10.5066/P9C7I13B
Landsat 4-5 TM Level-2:  https://doi.org/10.5066/P9IAXOVV

Masek, J.G., Vermote, E.F., Saleous N.E., Wolfe, R., Hall, F.G., Huemmrich, K.F., Gao, F., Kutler, J., and Lim, T-K. (2006). A Landsat surface reflectance dataset for North America, 1990–2000. IEEE Geoscience and Remote Sensing Letters 3(1):68-72. http://dx.doi.org/10.1109/LGRS.2005.857030.

Vermote, E., Justice, C., Claverie, M., & Franch, B. (2016). Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. Remote Sensing of Environment. http://dx.doi.org/10.1016/j.rse.2016.04.008.

Reprints or citations of papers or oral presentations based on USGS data are welcome to help the USGS stay informed of how data are being used. These can be sent to User Services at custserv@usgs.gov