Landsat surface temperature measures the Earth’s surface temperature in Kelvin and is an important geophysical parameter in global energy balance studies 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, wildfires), and urban heat island effects.
The surface temperature product is generated from the Landsat Collection 2 Level-1 thermal infrared bands, Top of Atmosphere (TOA) reflectance, TOA brightness temperature, 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 Goddard Earth Observing System (GEOS) Model Version 5 Forward Processing Instrument Teams (FP-IT) (for acquisitions from 2000 to present) or Modern Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) (for acquisitions from 1982 to 1999).
Global scene-based surface temperature data are available globally for the following instruments:
- Landsat 9 Operational Land Imager 2 (OLI-2): February 2022 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
Collection 2 Documentation
- Landsat 8-9 Collection 2 Level 2 Science Product Guide
- Landsat 4-7 Collection 2 Level 2 Science Product Guide
- Landsat Cloud Optimized GeoTIFF (COG) Data Format Control Book
- Landsat 8-9 OLI/TIRS Collection 2 Level 2 Data Format Control Book
- Landsat 7 ETM+ Collection 2 Level 2 Data Format Control Book
- Landsat 4-5 TM Collection 2 Level 2 Data Format Control Book
- Landsat 8-9 OLI Level-2 Science Products Digital Object Identifier (DOI): 10.5066/P9OGBGM6
- 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
Atmospheric Auxiliary Data
Collection 2 Surface Temperature 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 sources to use Collection 2 Level-2 products.
Visit Landsat Collection 2 Atmospheric Auxiliary for additional information.
Constraints and Caveats
Most Collection 2 Landsat 4-9 day-lit (descending acquisitions) surface reflectance scenes can be processed to a surface temperature product, but please note the following;
- Since ASTER GED data are used in the generation of the Landsat surface temperature product, when ASTER GED data are missing, there will be missing data in the ST product. Visit the Landsat Collection 2 Surface Temperature data gaps due to missing ASTER GED page to learn more about missing ASTER GED data in ST products.
- C2 ST products may display areas of 'blockiness' over small surface targets. Please access the Landsat Collection 2 Known Issues page to learn more.
- Since ASTER GED represents average emissivity for 2000-2008, the emissivity for any particular Landsat observation needs to be adjusted to the surface conditions at the time of Landsat overpass. An anomaly exists in vegetation adjustment of Landsat emissivity which results erroneous Surface Temperature values wherever NDVI has changed significantly between the ASTER and Landsat eras. Please access the Landsat Collection 2 Known Issues page to learn more.
- GEOS-5 FP-IT data are used to generate surface temperature products from 2000 to present. NASA’s MERRA-2 data are used to generate surface temperature products from 1982 to 1999.
- Atmospheric auxiliary data used for processing a Collection 2 Level-1 product into surface temperature are described in the Landsat Atmospheric Auxiliary Data Format Control Book.
- 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 surface temperature retrievals relative to clouds and possibly cloud shadows. The characterization of these issues has been documented by Cook et al., (2014).
- For Landsat 7 ETM+ products, Band 6 TOA BT and ST data are generated from ETM+ Band 6 High (6H) and 6 Low (6L) merged together. The merged band contains unsaturated pixels from Band 6H. If Band 6H pixels have a BT outside of the 6H dynamic range (240 to 322 Kelvin) then 6L band pixels are used. Pixels that are saturated in Band 6L remain saturated in the merged Band 6 product. The merged thermal radiance is then used in the creation of the TOA BT and ST data.
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 Landsat Data Access for additional data access and download options.
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, M. (2014). Atmospheric Compensation for a Landsat Land Surface Temperature Product. 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 Product from the archive. Remote Sensing, 6 (11), 11244-11266. https://www.mdpi.com/2072-4292/6/11/11244.
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 email@example.com
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, 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://www.usgs.gov/landsat-missions/landsat-science-team-meeting-july-22-24-2014.
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). https://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. https://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