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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, 2024, Vol. 21, No. 6, pp. 200-212

Development of mapping methods for wetland complexes in Western Siberia based on time series of remote sensing data and machine learning

S.S. Shinkarenko 1 , S.A. Bartalev 1 , E.A. Dyukarev 2, 3 , E.A. Golovatskaya 2 , I.A. Saigin 1 
1 Space Research Institute RAS, Moscow, Russia
2 Institute of Monitoring of Climatic and Ecological Systems SB RAS, Tomsk, Russia
3 Yugra State University, Khanty-Mansiysk, Russia
Accepted: 29.10.2024
DOI: 10.21046/2070-7401-2024-21-6-200-212
This article presents the results of mapping wetland complex types in Tomsk Region based on cloud-free time series of daily remote sensing (RS) data from the MODIS (Moderate Resolution Imaging Spectroradiometer). These data were utilized to create composite images of the Earth’s surface during periods of snow cover employing the Random Forest ensemble machine learning method. Additionally, digital elevation models such as GTOPO30, ASTER GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model) and FABDEM (Forest And Buildings removed Copernicus Digital Elevation Model) were used as features in the analysis. The developed peatland typology incorporates findings from other researchers and includes three wetland micro-landscapes with a tree cover (pine-shrub-sphagnum bog — pine bog (ryam), ryam-hollow complex, tree-shrub-moss-herb bog — swamp (sogra)), one complex type (ridge-hollow and ridge-lake complexes), two open types (herb-sphagnum bog, sedge-hypnum fen) and internal wetland lakes. The overall classification accuracy achieved was 0.96, with the completeness of identifying individual types of wetland complexes varying between 0.66 and 0.99. A total of 13.7 million hectares of wetland complexes were identified in Tomsk Region, including 9.4 million hectares predominantly classified as open wetlands. This estimate aligns well with statistical data indicating that the wetland area in the region is approximately 9.2 million hectares. The analysis demonstrates the high informational value of digital elevation models with varying spatial resolutions, as well as RS data collected during periods of snow cover presence and melt, and at the beginning and end of the vegetation period.
Keywords: wetlands, peatland, Tomsk Region, Western Siberia, MODIS, land cover, machine learning
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