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, 2019, Vol. 16, No. 5, pp. 130-137

Study of the tortuosity of the coastal boundaries of thermokarst lakes of Western Siberia using high-resolution images of Kanopus-V

Yu.M. Polishchuk 1, 2 , I.N. Muratov 1 , V.Yu. Polishchuk 3, 4 
1 Ugra Research Institute of Information Technology, Khanty-Mansiysk, Russia
2 Institute of Petroleum Chemistry SB RAS, Tomsk, Russia
3 Institute of Monitoring of Climatic and Ecological Systems SB RAS, Tomsk, Russia
4 Tomsk Polytechnic University, Tomsk, Russia
Accepted: 10.07.2019
DOI: 10.21046/2070-7401-2019-16-5-130-137
The paper is devoted to the issues of using high resolution images to study the properties and distribution of the tortuosity of the coastal boundaries of thermokarst lakes in the permafrost zone of Western Siberia. Remote studies were carried out on 78 test sites distributed fairly evenly over the territory of the cryolithozone of Western Siberia. To describe the tortuosity, an indicator of the shape of spatial objects adopted in cartography, which is calculated from the results of measuring the area and perimeter of lakes using satellite images, is used. The degree of tortuosity of the lake borders showed an average positive linear trend with an increase in the area of the lakes. A histogram of the distribution of the degree of tortuosity of the coastal boundaries of the lakes in a wide range of sizes from 50 m2 to 20 thousand hectares was constructed. Statistical analysis showed that the empirical distribution, according to the Pearson criterion, corresponded to the lognormal distribution law. The parameters of the log-normal law of the distribution of lake tortuosity according to empirical data were determined.
Keywords: permafrost, geoinformation systems, space images, degree of tortuosity of the lakes boundaries, lognormal distribution law
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