Surface temperature algorithm for data loss recovery Landsat 8–9 Collection 2 Level 2

DOI: 10.35595/2414-9179-2023-1-29-318-329

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About the Authors

Anna A. Gosteva

Federal Research Center Krasnoyarsk Science Center,
50, Akademgorodok, Krasnoyarsk, 660036, Russia,

Aleksandra K. Matuzko

Institute of Computational Modelling of the Siberian Branch of the Russian Academy of Sciences (ICM SB RAS),
50/44, Akademgorodok, Krasnoyarsk, 660036, Russia,

Oleg E. Yakubailik

Institute of Computational Modelling of the Siberian Branch of the Russian Academy of Sciences (ICM SB RAS),
50/44, Akademgorodok, Krasnoyarsk, 660036, Russia,


The use of thermal images for the analysis of urban areas is presented in Proceedings of InterCarto. InterGIS, on the example of the city of Krasnoyarsk according to Landsat 8 data. New Landsat 8–9 collection 2 level 2 data became available in March 2021. The data has been supplemented with valuable scientific products such as atmospheric parameters (atmospheric spectral transmittance, up-going radiation and down-going radiation), earth surface temperatures, thermal radiation, quality assessment mask. A detailed study of the data showed that for many territories previously studied by the authors, data were not provided in full. There is partial or complete loss of data in the emissivity layer, and as a consequence the loss is repeated in the Earth’s surface temperature layers. The same situation with data loss is observed in a number of other large Russian cities. The current situation required a detailed study of the documentation describing the Landsat 8–9 algorithms. Having studied all the stages of the algorithm execution, the authors managed to restore the sequence of calculations, while retaining additional atmospheric parameters. The lost data in the emissivity channel has been replaced with a new layer computed via NDVI. As a result, the authors tested the operation of the proposed algorithm on the territory of the city of Krasnoyarsk. The result of the algorithm execution is layers with surface temperature values without data loss, except for scenes with high cloudiness. There is a slight discrepancy between the surface temperature values when using the described algorithm and initial data, due to the use of different sources to determine the emissivity.


Landsat 8–9, temperature, remote sensing, LST GIS, thermal images


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For citation: Gosteva A.A., Matuzko A.K., Yakubajlik O.E. Surface temperature algorithm for data loss recovery Landsat 8–9 Collection 2 Level 2. InterCarto. InterGIS. GI support of sustainable development of territories: Proceedings of the International conference. Moscow: MSU, Faculty of Geography, 2023. V. 29. Part 1. P. 318–329. DOI: 10.35595/2414-9179-2023-1-29-318-329 (in Russian)