Landsat Science Products

Landsat Surface Reflectance

Landsat Surface Reflectance measures the fraction of incoming solar radiation reflected from Earth's surface to the Landsat sensor. 

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Landsat 8 Surface Reflectance example

Left: Landsat 8 Top of Atmosphere reflectance image (bands 4,3,2) and Right: Landsat 8 atmospherically corrected surface reflectance image for an area in Nepal, path 141 row 40 acquired on May 3, 2013.

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.

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

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

Please note that Level-2 Multi Spectral 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.

Collection 2 U.S. Analysis Ready Data (ARD) Surface Reflectance will be available in late 2020.

 

Landsat 8 Operational Land Imager (OLI)

Landsat 8 OLI surface reflectance are generated using the Land Surface Reflectance Code (LaSRC) algorithm (Version 1.4.1), which makes use of the coastal aerosol band to perform aerosol inversion tests, auxiliary climate data from MODIS, and a radiative transfer model (Vermote et al., 2016).

LaSRC hardcodes the view zenith angle to “0”. For the Solar Zenith and Solar Azimuth angles the scene center average value is used for atmospheric correction. 

Collection 2 Documentation (scene-based, global)

Collection 1 Documentation (U.S. Analysis Ready Data or on-demand via ESPA)

 

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

Landsat 4-5 TM and Landsat 7 ETM+ surface reflectance are generated using the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) algorithm (Version 3.4.0), 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 algorithm applies Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric correction routines to Landsat Collection 2 Level-1 data products. Water vapor, ozone, geopotential 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 Ttop of Aatmosphere (TOA) reflectance, surface reflectance, TOA brightness temperature, and masks for clouds, cloud shadows, adjacent clouds, land, and water.

Collection 2 Documentation (scene-based, global)

Collection 1 Documentation (U.S. Analysis Ready Data or on-demand via ESPA)

 

Surface Reflectance Algorithm Characteristics

The table below summaries the characteristic of the operational LEDAPS and LaSRC Collection 2 algorithms used by the USGS Landsat Product Generation System (LPGS).

 

Parameter Landsat 4-5, Landsat 7
(LEDAPS)
Landsat 8
(LaSRC)
Instrument Landsat 4-5 (TM), Landsat 7 (ETM+) Landsat 8
Landsat 9 (available 2021)
(Original) research grant NASA GSFC, MEaSUREs (Masek) NASA GSFC (Vermote)
Algorithm Version (USGS) 3.4.0 1.4.1
Global Coverage Yes Yes
Top of Atmosphere (TOA) Reflectance Visible (Bands 1–5,7) Visible (Bands 1–7, 9 OLI)
TOA Brightness Temperature Thermal (Band 6) Thermal (Bands 10 & 11 TIRS)
Surface Reflectance Visible (Bands 1-5, Band 7) Visible (Bandsat 1-7) (OLI only)
Thermal bands used in Surface Reflectance processing?  Yes
(Brightness temperature Band 6 is used in cloud estimation)
No
Radiative transfer model 6S Internal algorithm
Thermal correction level TOA only TOA only
Thermal band units Kelvin Kelvin
Pressure NCEP Grid Surface pressure is calculated internally based on the elevation
Water vapor NCEP Grid MODIS CMA
Air temperature NCEP Grid MODIS CMA
Digital Elevation Model GTOPO5  GTOPO5 
Ozone OMI/TOMS MODIS CMG Coarse resolution ozone
Aerosol Optical Thickness (AOT) Correlation between chlorophyll absorption
and bound water absorption of scene
MODIS CMA
Sun angle Scene center from input metadata Scene center from input metadata
View zenith angle From input metadata Hard-coded to "0"
Undesirable zenith angle correction SR not processed when solar zenith angle
> 76 degrees
SR not processed when solar zenith angle > 76 degrees
Pan band processed? No No
Metadata MTL, XML, STAC MTL, XML, STAC
Top of Atmosphere
Brightness Temperature calculated
Yes (Band 6 TM/ETM+) Yes (Band 10 & 11 TIRS)
Cloud mask CFMask (Version 3.3.1) CFMask (Version 3.3.1)
Data format Unsigned 16-bit integer Unsigned 16-bit integer
Fill values 0 0
QA bands Cloud
Adjacent cloud
Cloud shadow
DDV
Fill
Land water
Snow
Atmospheric opacity
Cloud
Adjacent cloud
Cloud shadow
Aerosols
Cirrus
Aerosol Interpolation

6S- Second Simulation of a Satellite Signal in the Solar Spectrum, CFmask- C Version of Function Of Mask, CMA- Climate Modeling Grid - Aerosol, CMG- Climate Modeling Grid, DDV- Dark Dense Vegetation, MEaSUREs- Making Earth Science Data Records for Use in Research Environments, MODIS- Moderate Resolution Imaging Spectroradiometer, OMI- Ozone Monitoring Instrument, QA Quality Assessment, TOMS- Total Ozone Mapping Spectrometer

 

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.

Note: Collection 1 surface reflectance atmospheric auxiliary data are not available for download.

 

Constraints and Caveats 

Most day-lit (descending) Landsat 4-8 scenes in the USGS archive can be processed to Surface Reflectance. Newly-collected Landsat 8 and Landsat 7 Real-Time scenes become suitable for processing within a few days of data acquisition.

Please note the following constraints and caveats: 

1. Missing Input Data. Due to missing Landsat Level-1 and/or required auxiliary input data, surface reflectance processing cannot be applied to scenes acquired during the dates listed below: 

  • Landsat 8
    • 2019: December 19-20 (partial DOY 353 to partial DOY 354)
      Missing Level-1 input data due to satellite safehold. Visit this Landsat Headline to see the path/pows affected. 
  • Landsat 7
    • 2016: May 30 to June 12 (DOY 151 to 164) — Auxiliary data unavailable
    • 2017: March 12 to March 17 (DOY 71 to 76) — Auxiliary data unavailable

2. Low Sun Angle and Cloud Contamination. The efficacy of land surface reflectance correction is likely to be reduced in hyper-arid or snow-covered regions, areas with low sun angle conditions, coastal regions where land area is small, relative to adjacent water, or areas with extensive cloud contamination.

Corrections may not be accurate to data acquired over high latitudes (> 65 degrees North or South). Landsat 7 ETM+ inputs are not gap-filled in the surface reflectance production. Users can refer to the Quality Assessment (QA) band for pixel-level condition and validity flags.

3. Extreme Low Radiance, Exteme Bright Targets. Landsat atmospheric correction and surface reflectance retrieval algorithms are not ideal for water bodies due to the inherently low level of water leaving radiance, and the consequential very low signal to noise ratio. Similarly, surface reflectance values greater than 1.0 can be encountered over bright targets such as snow and playas. These are known computational artifacts in the Landsat surface reflectance products.  

Quantitative remote sensing retrievals of water column constituents requires different algorithms, which are being considered for integration into future Landsat surface reflectance products.

 

Data Access

Collection 2 Surface Reflectance data: Landsat Collection 2 Level-2 data will be available from EarthExplorer and LandsatLook. The USGS Landsat no-cost and 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. For individual scene downloads, two or more band files will be grouped in a .tar file in order to provide a single 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).

Collection 1 Surface Reflectance data (on-demand): Processing requests for scene-based Landsat Surface Reflectance data can be submitted from EarthExplorer. The data are located under the Landsat category, Landsat Collection 1 Level-2 (On-Demand)subcategory, with Landsat 8, Landsat 7, and Landsat 4-5 TM listed as individual datasets. These requests are sent to the USGS Earth Resources Observation and Science (EROS) Center Science Processing Architecture (ESPA) On Demand Interface (ESPA) On-Demand Interface for processing and data delivery.

The ESPA can also be used to submit lists of Landsat Level-1 scenes or granules from select MODIS collections to request Level-2 Surface Reflectance processing, Surface Reflectance-based spectral indices, customize output options, and request output product statistics and plots. 

U.S. ARD Surface Reflectance data: Tile-based Surface Reflectance data are available for immediate download; the data are located under the Landsat category, Landsat Analysis Ready Data (ARD) subcategory, and listed as U.S. Landsat 4-8 ARD.

Visit the Landsat Data Access webpage for additional data access and 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) ToolsDeveloped by the MODIS land quality assessment group to work specifically with Landsat Surface Reflectance data. 

 

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

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

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