Landsat Science Products

Landsat Provisional Surface Temperature

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Landsat Surface Temperature

Left: Surface Reflectance image (bands 5,4,3) and Right: color-enhanced Provisional Landsat Surface Temperature for an area within CONUS ARD tile h005v013 (WRS Path 38 Row 37) acquired on August 16, 2000. Light areas in the Surface Temperature image indicate cooler temperatures; darker areas indicate warmer temperatures.

Landsat Level-2 Provisional Surface Temperature products are included in the U.S. Landsat Analysis Ready Data (ARD) product bundle.

Provisional Surface Temperature measures the temperature of the surface of the Earth in Kelvin (K) and is an important parameter in energy balance and hydrologic modeling. Surface Temperature data are also useful for monitoring crop and vegetation health, and extreme heat events such as, natural disasters (e.g., volcanic eruptions, wild fires), and urban heat island studies.

The Landsat Provisional Surface Temperature product is generated from the Landsat Collection 1 Level-1 thermal infrared bands, Top of Atmosphere (TOA) Reflectance, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Database (GED) data, ASTER Normalized Difference Vegetation Index (NDVI) data, and atmospheric profiles of geopotential height, specific humidity, and air temperature extracted from reanalysis data.

The Landsat Provisional Surface Temperature product is processed to 30-meter spatial resolution in Albers Equal Area (AEA) projection using the World Geodetic System 1984 (WGS84) datum and gridded to a common tiling scheme. Product is delivered in Georeferenced Tagged Image File Format (.tif) files.

Current Algorithm Version

Note: The Landsat Surface Temperature Science Product has reached a provisional level of maturity for the United States, meaning that its uncertainties are understood in multiple locations and assessments of its results have demonstrated positive science value.  Algorithm artifacts have been identified under certain observational conditions, and are currently being analyzed to develop and test solutions to enhance algorithmic implementation, reduce uncertainty, and improve future surface temperature products. Current algorithm performance is documented in the peer-reviewed literature listed on this web page and in the product guide.

The USGS is requesting that users of the surface temperature product  – before it is declared operational – include the following disclaimer: "USGS Landsat Surface Temperature Science Product may report unvalidated results for certain observational conditions."

Product Availability

Landsat Provisional Surface Temperature data are available for the conterminous U.S., Alaska, and Hawaii and for the following date ranges:

  • Landsat 8 OLI: April 2013 to present
  • Landsat 7 ETM+: July 1999 to present
  • Landsat 5 TM: March 1984 to May 2012
  • Landsat 4 TM: July 1982 to December 1993

Package Content

The Landsat Provisional Surface Temperature file package contains two primary raster products and several intermediate bands used by the Surface Temperature algorithm, to represent the temperature of the Earth’s land surface in Kelvin (K), as well as quality assessment information. The Surface Temperature file package includes a metadata file in Extensible Markup Language (.xml) format.

The list below describes the products and filenames that are delivered with the Landsat Surface Temperature package.

Surface Temperature (ST): Represents the temperature of the Earth’s surface in Kelvin (K).
Delivered file name:  *_ST.tif
Approximate file size: 9.1 MB

Surface Temperature Quality Assessment (STQA): Provides the Surface Temperature product uncertainty using a combination of uncertainty values and distance to cloud values.
Delivered file name:*_STQA.tif
Approximate file size: 8.1 MB

Atmospheric Transmittance layer (ATRAN): Displays the ratio of the transmitted radiation to the total radiation incident upon the medium (atmosphere).
Delivered file name: *_ATRAN.tif
Approximate file size: 1.5 MB

Emissivity layer (EMIS): Displays the ratio of the energy radiated from a material’s surface to that radiated from a blackbody.
Delivered file name:*_EMIS.tif
Approximate file size: 15.6 MB

Emissivity Standard Deviation (EMSD): The extent of deviation of the emissivity product. This layer is used along with CDIST to create the STQA product. 
Delivered file name:*_EMSD.tif
Approximate file size: 4.9 MB

Upwelled Radiance layer (URAD): Displays the amount of electromagnetic radiation reflected upward from the ground’s surface.
Delivered file name: *_URAD.tif
Approximate file size: 1.5 MB

Downwelled Radiance layer (DRAD): Displays the thermal energy radiated onto the ground by all objects in a hemisphere surrounding it.
Delivered file name: *_DRAD.tif
Approximate file size: 1.5 MB

Thermal Radiance layer (TRAD): Displays the values produced when thermal band reflectance is converted to radiance.
Delivered file name: *_TRAD.tif
Approximate file size: 1.5 MB

Distance to Cloud (CDIST): Represents the distance, in kilometers, that a pixel is from the nearest cloud pixel. This layer is used along with EMSD to create the STQA product.
Delivered file name:*_CDIST.tif
Approximate file size: 5.4 MB

Caveats and Constraints

Most Landsat Collection 1 Level-1 scenes can be processed to generate a Surface Temperature product. In addition to the caveats listed on the Landsat ARD page, please note the following:

  • The Landsat Provisional Surface Temperature product will occasionally include missing data, particularly over both inland and coastal waters, due to missing data in the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Database (GED).
  • The Landsat Surface Temperature product is geographically limited within the boundary of the North American Regional Reanalysis (NARR) grid (see the Surface Temperature Product Guide), which is the climate data set used in the atmospheric correction algorithm.
  • Data products must contain both optical and thermal data (e.g., LC08 products for Landsat 8) to be successfully processed to Surface Temperature, as ASTER NDVI is required to temporally adjust the ASTER GED product to the target Landsat scene. Therefore, night time acquisitions cannot be processed to Surface Temperature.
  • A known error exists in the Landsat Surface Temperature retrievals relative to clouds and possibly cloud shadows. The characterization of these issues has been documented by Cook et al., 2014 (see the References section for more details).

Data Access

The Landsat Provisional Surface Temperature product is available for download from EarthExplorerThe 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 web page for information about bulk download options.  

Documentation

Landsat Provisional Surface Temperature Product Guide

Landsat Analysis Ready Data (ARD) Data Format Control Book (DFCB)

Landsat Provisional Surface Temperature (ST) Digital Object Identification (DOI): doi.org/10.5066/F7J38RTH

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 Temperature Science Product courtesy of the U.S. Geological Survey.

Cook, Monica J., "Atmospheric Compensation for a Landsat Land Surface Temperature Product" (2014). Thesis. Rochester Institute of Technology. Accessed from http://scholarworks.rit.edu/theses/8513.

Cook, M., Schott, J. R., Mandel, J., & Raqueno, N. (2014). Development of an operational calibration methodology for the Landsat thermal data archive and initial testing of the atmospheric compensation component of a Land Surface Temperature (LST) Product from the archive. Remote Sensing, 6(11), 11244-11266. http://dx.doi.org/10.3390/rs61111244.

References

Berk, A., Anderson, G. P., Acharya, P. K., Bernstein, L. S., Muratov, L., Lee, J., ... & Lockwood, R. B. (2005, June). MODTRAN 5: a reformulated atmospheric band model with auxiliary species and practical multiple scattering options: update. In Defense and Security (pp. 662-667). International Society for Optics and Photonics. http://dx.doi.org/10.1117/12.606026.

Cook, Monica J., "Atmospheric Compensation for a Landsat Land Surface Temperature Product" (2014). Thesis. Rochester Institute of Technology. Accessed from http://scholarworks.rit.edu/theses/8513.

Cook, M., Schott, J. R., Mandel, J., & Raqueno, N. (2014). Development of an operational calibration methodology for the Landsat thermal data archive and initial testing of the atmospheric compensation component of a Land Surface Temperature (LST) Product from the archive. Remote Sensing, 6(11), 11244-11266. http://dx.doi.org/10.3390/rs61111244

Cook, M., & Schott, J. R. (2014). Atmospheric Compensation for a Landsat Land Surface Temperature Product. Landsat Science Team Meeting, July 22-24, 2014; Corvallis, Oregon, USA. Accessed from https://landsat.usgs.gov/sites/default/files/documents/Schott_LST_LLST.pdf.

Hulley, G. C., Hughes, C. G., & Hook, S. J. (2012). Quantifying uncertainties in land surface temperature and emissivity retrievals from ASTER and MODIS thermal infrared data. Journal of Geophysical Research: Atmospheres (1984–2012), 117(D23). http://dx.doi.org/10.1029/2012JD018506.

Hulley, G. C., Hook, S. J., Abbott, E., Malakar, N., Islam, T., & Abrams, M. (2015). The ASTER Global Emissivity Dataset (ASTER GED): Mapping Earth's emissivity at 100 meter spatial scale. Geophysical Research Letters, 42(19), 7966-7976. http://dx.doi.org/10.1002/2015GL065564.

Laraby, K. G., Schott, J. R. (2018). Uncertainty estimation method and Landsat 7 global validation for the Landsat surface temperature product. Remote Sensing of Environment, 216, 472-481.https://doi.org/10.1016/j.rse.2018.06.026 

Laraby, K. G., Schott, J. R., & Raqueno, N. (2016). Developing a confidence metric for the Landsat land surface temperature product. Proc. SPIE 9840, Algorithms and Technologies for Multispectral, Hyperspectral and Ultraspectral Imagery, XXII, 98400C. http://dx.doi.org/10.1117/12.2222582.

Malakar, N. K., Hulley, G. C., Hook, S. J., Laraby, K., Cook, M., & Schott, J. R. (2018). An Operational Land Surface Temperature Product for Landsat Thermal Data: Methodology and Validation. IEEE Transactions on Geoscience and Remote Sensing, (99), 1-19. http://dx.doi.org/10.1109/TGRS.2018.2824828.

Mesinger, F., DiMego, G., Kalnay, E., Mitchell, K., Shafran, P. C., Ebisuzaki, W., ... & Ek, M. B. (2006). North American regional reanalysis. Bulletin of the American Meteorological Society, 87(3), 343-360. http://dx.doi.org/10.1175/BAMS-87-3-343.

Schaeffer,  B. A., Iiames,  J., Dwyer,  J., Urquhart,  E., Salls,  W., Rover,  J., & Seegers,  B., (2018). An initial validation of Landsat 5 and 7 derived surface water temperature for U.S. lakes, reservoirs, and estuaries, International Journal of Remote Sensing, https://dx.doi.org/10.1080/01431161.2018.1471545

 

 

 

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