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Using thermal remote sensing in the classification of mountain permafrost landscapes

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Abstract

Thermal infrared satellite imagery is increasingly utilized in permafrost studies. One useful application of the land surface temperature (LST) products is classification and mapping of landscapes in permafrost regions, as LST values can help differentiate between frozen and unfrozen ground. This article describes a new approach to the use of LST. The essence of the new approach lies in the fact that in the territory where it is impossible to determine (indicate) the state of the underlying ground according to the same morphological characteristics (relief, vegetation, soil composition, etc.), the LST parameter, which reflects the thermal state of the landscape, allows as an additional criterion (indicator) identify frozen/un-frozen landscapes. In this work, using the above approach, a map has been compiled, which shows the permafrost natural-territorial complexes of the Elkon Massif, Eastern Siberia, including topography, slope aspect, slope angle, vegetation, snow cover and LST. The map provides a more detailed and updated description of permafrost distribution in the study area.

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Acknowledgments

We express our gratitude to A.N. Fedorov for help and advice on the classification of permafrost landscapes, to M. N. Zheleznyak and A.R. Kirillin for providing in-situ data on ground temperature and snow cover.

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Authors and Affiliations

  1. Melnikov Permafrost Institute, Siberian Branch of Russian Academy of Sciences, Yakutsk, 677010, Russia

    Svetlana V. Kalinicheva & Alyona A. Shestakova

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  1. Svetlana V. Kalinicheva
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  2. Alyona A. Shestakova
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Correspondence to Svetlana V. Kalinicheva.

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Kalinicheva, S.V., Shestakova, A.A. Using thermal remote sensing in the classification of mountain permafrost landscapes. J. Mt. Sci. 18, 635–645 (2021). https://doi.org/10.1007/s11629-020-6475-7

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  • DOI: https://doi.org/10.1007/s11629-020-6475-7

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