Landsat Collection 2 Provisional Aquatic Reflectance Science Product

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Landsat’s moderate spatial resolution provides the capability to map optically active components of upper water column in inland and near-shore waters. Ocean color, defined as the spectral distribution of reflected visible solar radiation upwelling from beneath the water surface, has revolutionized the field of aquatic remote sensing research. The applications of ocean color remote sensing are extensive and fundamental to understanding and monitoring both marine and freshwater ecosystems.

Landsat Collection 2 (C2) Provisional Aquatic Reflectance (AR) products are derived from Landsat 8-9 Operational Land Imager (OLI) Level-1 (L1) reflective bands over water pixels at a 30-meter resolution. Landsat Top of Atmosphere (TOA) Reflectance and auxiliary atmospheric data are required inputs into the atmospheric correction algorithm to retrieve the water-leaving radiance at visible wavelengths. The water-leaving radiances are then normalized by downwelling solar irradiance to remove the remaining effects of solar orientation and atmospheric attenuation to produce spectral Remote Sensing Reflectance (R_rs) bands. Finally, the R_rs bands are normalized by the Bidirectional Reflectance Distribution Function (BRDF) of a perfectly reflecting Lambertian surface (multiplied by π) to produce the dimensionless Aquatic Reflectance. The methodologies used in this algorithm are directly derived from the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System (SeaDAS) package distributed by NASA’s Ocean Biology Processing Group (OBPG) and modified by the USGS to process Landsat 8-9 OLI sensor data.

Landsat 8-9 C2 Provisional AR products are processed for Visible and NIR bands (VNIR) (Bands 1-5 for Landsat 8-9 OLI). Intermediate Rayleigh-corrected reflectances (RHORC) for Visible to Shortwave Infrared (VSWIR) Bands 1-7 that were used as input for Aquatic Reflectance processing are also delivered. Please refer to the Landsat 8-9-Collection 2 Provisional Aquatic Refectance Product Guide for more details about AR processing.

The atmospheric auxiliary data required for the successful processing of the Landsat 8-9 C2 Provisional AR are described in the Auxiliary Data section below on this page.

Note: These data are provisional and are subject to revision. They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the data.

Product Availability

Landsat 8-9 C2 Provisional AR products are available globally from March 2013 to present, for Landsat 8-9 OLI data. Thermal data are not required to successfully process AR, so both Landsat 8 and Landsat 9 Combined (LC08/LC09) and OLI-only (LO08/LO09) data can be processed to C2 AR.  See the Caveats and Constraints section below for those data that cannot be processed to C2 AR.

Atmospheric Auxiliary Data Used in C2 Provisional AR Products

The following atmospheric auxiliary data are used in the creation of Landsat C2 Provisional AR products:

• National Centers for Environmental Prediction (NCEP) Meteorological (MET) data: contains zonal wind, meridional wind, atmospheric pressure at mean sea level, relative humidity, and water vapor information.
• Total Ozone Mapping Spectrometer (TOMS)/ Ozone Monitoring Instrument (OMI) ozone: provides ozone, aerosol and reflectivity measurements.
• National Snow and Ice Data Center (NSIDC) sea ice extent: provides measurements of daily sea ice extent and sea ice edge boundaries.

More details about the atmospheric auxiliary data used in C2 AR processing can be found in the Landsat 8-9 Collection 2 Provisional Aquatic Reflectance Algorithm Description Document.

Improvements and Changes from Collection 1 

Listed below are items that have been improved and/or changed in C2 Provisional AR, compared to Collection 1 Provisional AR products:

• Availability of Landsat 9 C2 Provisional AR products
• Addition of intermediate Rayleigh-corrected reflectance data for VSWIR bands (Bands 1-7)
• Addition of atmospheric auxiliary input bands for more accurate calculations
• Addition of per-pixel Level-1 solar/sensor viewing zenith and azimuth angles in addition to the scattering angle based on these angles
• Addition of a Water Mask band for improved water pixel classification

Package Contents

Landsat 8-9 C2 Provisional AR products are delivered inside of a .tar file, in a compressed zip file (tar.gz) named in a similar fashion to other Landsat products available from ESPA. The compressed file contains 24  individual raster files and one metadata file, listed below. Additional specifications and attributes for these files can be found in Section 3 of the Landsat 8-9 Collection 2 Provisional Aquatic Refectance Product Guide.

• Aquatic Reflectance (AR_BAND#, for Bands 1 through 5): Represents the nondimensional aquatic (water-leaving) reflectance, assuming a perfectly Lambertian surface.
• Rayleigh-corrected Reflectance (RHORC_BAND#, for Bands 1 through 7): Represents the intermediate Rayleigh-corrected reflectance, which is then used to generate AR.
• Auxiliary bands (WATER_VAPOR, PRESSURE, WINDSPEED, NO2_TROPO): Represents atmospheric input information used for Aquatic Reflectance  and Rayleigh calculations.
• Processing flags band (L2_FLAGS): A bit-packed band that provides per-pixel information about success or failure of processing and validity of sun glint, view angle, solar angle, polarization and chlorophyll-a.
• Level-1 Pixel Quality Band (QA_PIXEL):  The bit combinations that define certain quality conditions.
• Water Mask (WATER_MASK): Classified raster consisting of pixels identified as land (0), water (1), cloud (2), cloud shadow (3) and snow (4) used for masking non-water pixels in the RHORC and AR bands.
• Solar and Sensor angle files (SAA, SZA, VAA, VZA, SCATTANG) – Per-pixel Level-1 solar/sensor viewing zenith and azimuth angles in addition to the scattering angle based on these angles. These angles are valuable for chlorophyll-a retrievals.
• Angle Band Coefficients File (ANG) – Text (.txt) document containing input information to generate the per-pixel sensor and sun viewing angle bands.
• Metadata: Includes Aquatic Reflectance Science Product information in XML format (Product_ID.xml) and Level-1 metadata both in .txt and XML format.

Caveats and Constraints 

The items listed below are brief descriptions of the known restrictions regarding C2 Provisional AR processing; please refer to the Caveats and Constraints section of the Landsat 8-9 Collection 2 Provisional Aquatic Refectance Product Guide for more details about each item.

1. Current Landsat 8-9 C2 AR science products are considered provisional. The atmospheric correction algorithm and subsequent output products have not been completely validated.
2. This provisional AR science product currently is available only for Landsat 8-9 Collection 2 Operational Land Imager (OLI) data; the capability to process Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 4-5 Thematic Mapper (TM), and Sentinel-2 Multispectral Instrument (MSI) data likely will be added in the future.
3. An across-track non-uniformity artifact may be visible in this product; mainly due to slight differences in the viewing geometries of odd and even Focal Plane Modules (FPM) of OLI in along-track direction.
4. This product uses an algorithm developed internally at USGS EROS to assess each pixel for the presence of water. This procedure may result in omission and commission classification errors. The commission error will trigger AR processing for non-water pixels. Using the AR product should be restricted to only water pixels.
5. The QA_PIXEL band is used for masking cloud, cloud shadow and snow. The Rayleigh-corrected Reflectance (RHORC) and AR product bands may include instances where ‘NoData’ values appear over valid water pixels. ‘NoData’ pixels are usually due to misclassified clouds resulting from the Fmask operation over water. For more information on Fmask algorithm, see https://www.usgs.gov/landsat-missions/cfmask-algorithm. Any ‘NoData’ pixel in the AR that has valid RHORC value is due to aerosol correction failure.
6. Due to missing auxiliary input data, Aquatic Reflectance processing cannot be applied to data acquired during the dates listed below.

Data Access

Landsat 8-9 C2 Provisional AR science products are available from the USGS EROS Science Processing Architecture (ESPA) On-demand Interface. A valid Landsat 8 or Landsat 9 Level-1 Combined (LC08/LC09) or OLI-Only (LO08/LO09) product ID must be submitted to process C2 Provisional AR products. 

The default projection system for all Landsat science products is Universal Transverse Mercator (UTM), but another projection can be selected. The default file format is Georeferenced Tagged Image File Format (GeoTIFF), but other data formats are available. ESPA also offers additional customization services such as spatial subsetting, and pixel resizing. More information about ESPA’s processing options can be found in the ESPA On-Demand Interface User Guide. Information about bulk downlod options can be found on the Landsat Data Access web page.

Documentation

• Landsat 8-9 Collection 2 Provisional Aquatic Reflectance Product Guide
• Landsat 8-9 Collection 2 Provisional Aquatic Reflectance Algorithm Description Document (ADD)

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 8-9 Collection 2 Provisional Aquatic Reflectance product is courtesy of the U.S. Geological Survey.

The Landsat 8-9 Collection 2 Provisional Aquatic Reflectance product is based directly on work described in:

• Franz, B.A., Bailey, S.W., Kuring, N., & Werdell, P.J. (2015). Ocean color measurements with the Operational Land Imager on Landsat-8: implementation and evaluation in SeaDAS. Journal of Applied Remote Sensing, 9(1), 096070. https://doi.org/10.1117/1.JRS.9.096070
• Pahlevan, N., Schott, J.R., Franz, B.A., Zibordi, G., Markham, B., Bailey, S., Schaaf, C.B., Ondrusek, M., Greb, S. & Strait, C.M. (2017). Landsat 8 remote sensing reflectance (R_rs) products: Evaluations, intercomparisons, and enhancements. Remote sensing of environment, 190, 289-301. https://doi.org/10.1016/j.rse.2016.12.030

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 custserv@usgs.gov.

References

• Kabir, S., Pahlevan, N., O’Shea, R., & Barnes, B. B. (2023). Leveraging Landsat-8/-9 underfly observations to evaluate consistency in reflectance products over aquatic environments. Remote Sensing of Environment, 296, 113755. https://doi.org/10.1016/j.rse.2023.113755

• Pahlevan, N., Mangin, A., Balasubramanian, S.V., Smith, B., Alikas, K., Arai, K., Barbosa, C., Bélanger, S., Binding, C., Bresciani, M. and Giardino, C., 2021. ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters. Remote Sensing of Environment, 258, p.112366. https://doi.org/10.1016/j.rse.2021.112366
• Ilori, C.O., Pahlevan, N., & Knudby, A., 2019. Analyzing Performances of Different Atmospheric Correction Techniques for Landsat 8: Application for Coastal Remote Sensing. Remote Sensing, 11, 469. https://doi.org/10.3390/rs11040469
• Pahlevan, N., Schott, J.R., Franz, B.A., Zibordi, G., Markham, B., Bailey, S., Schaaf, C.B., Ondrusek, M., Greb, S. & Strait, C.M., 2017. Landsat 8 remote sensing reflectance (Rrs) products: Evaluations, intercomparisons, and enhancements. Remote sensing of environment, 190, 289-301. https://doi.org/10.1016/j.rse.2016.12.030
• Mobley, C.D., Werdell, J., Franz, B., Ahmad, Z., & Bailey, S., 2016. Atmospheric correction for satellite ocean color radiometry. NASA Tech. Memo, NASA/TM-2016-217551, p. 85 https://ntrs.nasa.gov/search.jsp?R=20160011399
• Morfitt, R., Barsi, J., Levy, R., Markham, B., Micijevic, E., Ong, L., Scaramuzza, P. and Vanderwerff, K., 2015. Landsat-8 Operational Land Imager (OLI) radiometric performance on-orbit. Remote Sensing, 7(2), pp.2208-2237. https://doi.org/10.3390/rs70202208
• Franz, B.A., Bailey, S. W., Kuring, N., & Werdell, P.J., 2015. Ocean color measurements with the Operational Land Imager on Landsat-8: implementation and evaluation in SeaDAS. Journal of Applied Remote Sensing, 9(1), 096070. https://doi.org/10.1117/1.JRS.9.096070
• Pahlevan, N., Lee, Z., Wei, J., Schaaf, C.B., Schott, J.R. and Berk, A., 2014. On-orbit radiometric characterization of OLI (Landsat-8) for applications in aquatic remote sensing. Remote Sensing of Environment, 154, pp.272-284.
• Pahlevan, N., & Schott, J.R., 2013. Leveraging EO-1 to evaluate capability of new generation of Landsat sensors for coastal/inland water studies. IEEE Journal of selected topics in applied earth observations and remote sensing, 6(2), 360-374. https://doi.org/10.1109/JSTARS.2012.2235174
• Gordon, H.R., & Wang, M., 1994. Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: a preliminary algorithm. Applied optics, 33(3), 443-452. https://doi.org/10.1364/AO.33.000443