Mapping Siberian Arctic Mountain Permafrost Landscapes by Machine Learning Multi-sensors Remote Sensing: Example of Adycha River Valley

Moisei Zakharov, Moisei Zakharov, Sébastien Gadal, Sébastien Gadal, Yuri Danilov, Jūratė Kamičaitytė

2021

Abstract

The landscape taxonomy has a complex structure and hierarchical classification with indicators of their recognition, which is based on a variety of heterogeneous geographic territorial and expert knowledge. This inevitably leads to difficulties in the interpretation of remote sensing data and image analysis in landscape research in the field of classification and mapping. This article examines an approach to the analysis of intra-season Landsat 8 OLI images and modeling of ASTER GDEM data for mapping of mountain permafrost landscapes of Northern Siberia at the scale of 1: 500,000 as well as its methods of classification and geographical recognition. This approach suggests implementing the recognition of terrain types and vegetation types of landscape types. The 8 types of the landscape have been identified by using the classification of the relief applying Jenness's algorithm and the assessment of the geomorphological parameters of the valley. The 6 vegetation types have been identified in mountain tundra, mountain woodlands, and valley complexes of the Adycha river valley in the Verkhoyansk mountain range. The results of mapping and the proposed method for the interpretation of remote sensing data used at regional and local levels of studying the characteristics of the permafrost distribution. The work contributes to the understanding of the landscape organization of remote mountainous permafrost areas and to the improvement of methods for mapping the permafrost landscapes for territorial development and rational environmental management.

Paper Citation

in Harvard Style

Zakharov M., Gadal S., Danilov Y. and Kamičaitytė J. (2021). Mapping Siberian Arctic Mountain Permafrost Landscapes by Machine Learning Multi-sensors Remote Sensing: Example of Adycha River Valley. In Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM, ISBN 978-989-758-503-6, pages 125-133. DOI: 10.5220/0010448801250133

in Bibtex Style

@conference{gistam21,
author={Moisei Zakharov and Sébastien Gadal and Yuri Danilov and Jūratė Kamičaitytė},
title={Mapping Siberian Arctic Mountain Permafrost Landscapes by Machine Learning Multi-sensors Remote Sensing: Example of Adycha River Valley},
booktitle={Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,},
year={2021},
pages={125-133},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010448801250133},
isbn={978-989-758-503-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,
TI - Mapping Siberian Arctic Mountain Permafrost Landscapes by Machine Learning Multi-sensors Remote Sensing: Example of Adycha River Valley
SN - 978-989-758-503-6
AU - Zakharov M.
AU - Gadal S.
AU - Danilov Y.
AU - Kamičaitytė J.
PY - 2021
SP - 125
EP - 133
DO - 10.5220/0010448801250133