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Open-Source Software Implementation and Validation of the Split-Window Method for Automated Land Surface Temperature Retrieval from Landsat 8 Data

  • METHODS AND PROCESSING TOOLS AND INTERPRETATION OF SPACE INFORMATION
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Abstract

An open software implementation of the algorithm for retrieving the land surface temperature (LST) from Landsat 8 remote sensing satellite data is presented using the split-window algorithm, supplemented by a covariance-variational technique to modeling the water-vapor content in the atmosphere. The implementation also uses the Simplified and Robust Surface Reflectance Estimation Method (SREM), a physical-based atmospheric correction method, and the FMASK cloud and cloud-shadow detection algorithm. All components of the complex algorithm are fully automated and do not require additional information, including external data on the state of the atmosphere. The implementation of the algorithm has been validated at various settings on the basis of ten ground stations in the United States that publish data on observations of the LST with a high time resolution; the average absolute error according to its results was 1.1°C. The software component is developed in Python and is available in the public repository https://github.com/eduard-kazakov/Landsat8_LST_PSWA; the source code is distributed under an open license.

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Authors and Affiliations

  1. State Hydrological Institute, 199053, St. Petersburg, Russia

    E. E. Kazakov & Yu. I. Borisova

  2. St. Petersburg State University, 199034, St. Petersburg, Russia

    Yu. I. Borisova

Authors
  1. E. E. Kazakov
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  2. Yu. I. Borisova
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Correspondence to E. E. Kazakov.

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Translated by V. Selikhanovich

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Kazakov, E.E., Borisova, Y.I. Open-Source Software Implementation and Validation of the Split-Window Method for Automated Land Surface Temperature Retrieval from Landsat 8 Data. Izv. Atmos. Ocean. Phys. 57, 1171–1178 (2021). https://doi.org/10.1134/S0001433821090504

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