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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2026. Т. 23. № 3. С. 96-108

Effectiveness of methods for extracting ground surface temperature from Landsat data for northern Siberian landscapes

A.A. Karsakov 1 , E.I. Ponomarev 1 
1 Krasnoyarsk Science Center SB RAS, Krasnoyarsk, Russia
Accepted: 25.03.2026
DOI: 10.21046/2070-7401-2026-23-3-96-108
Land Surface Temperature (LST) is a critical parameter that is derived from remote sensing data and is frequently employed to evaluate the condition of natural ecosystem components and heat exchange processes within the soil–vegetation–atmosphere system. This study evaluates the efficiency of various LST retrieval methods using multi-year Landsat data. In northern Siberia, the characteristic landscapes of the cryolithozone were analyzed based on the observed LST ranges. The findings show that for natural landscapes, techniques based on the Radiative Transfer Equation (RTE) have high internal consistency (mean coefficient of variation CV = 4.2…6.8%; median shift ≤1.2 °C). The degree of uncertainty increases substantially for the “Infrastructure” class (CV = 12.4…15.7%), which is attributed to limitations of NDVI-dependent land surface emissivity (LSE) models when applied to intrazonal land cover types (NDVI = 0.21…0.48). The Quantum Geographic Information Systems (QGIS) Semi-Automatic Classification Plugin (SCP) employs a method that consistently underestimates LST values in comparison to RTE-based approaches (up to –40% in 2022). This suggests that the built-in LSE model is not suitable for cryolithozone landscapes. The Sobrino et al. method (Sobrino et al., 2008), in conjunction with alternative RTE-based approaches to quantify uncertainty levels, was found to be the most effective method for monitoring the thermal dynamics of industrially transformed landscapes under Arctic conditions. The utilization of QGIS SCP necessitates preliminary calibration with local reference data. The findings can be employed to enhance satellite data processing algorithms for environmental monitoring in northern Siberian landscapes.
Keywords: Land Surface Temperature, LST, satellite imagery, underlying surface, landscape, cryolithozone, post-industrial transformation of landscape, oil and gas complex
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