Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery

Tatiana G. Plutalova*, Kanayim Teshebaeva, Dmitry N. Balykin, Alexander V. Puzanov, Jacobus van Huissteden, Mikhail I. Koveshnikov, Olga V. Lovtskaya, Nelly M. Kovalevskaya

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

In this study fusion of optical (Sentinel-2) and radar (Sentinel-1) imagery is presented for vegetation cover classification in polar Arctic environment of the Western Siberia. Sentinel-1 and Sentinel-2 images were analyzed using parametric rule classification. Results showed significantly improved land cover classification results based on contextual analysis. Synergy of Sentinel-2 bands 4 and 3 and Sentinel-1 dual polarization VV and VH images increased the classification accuracy significantly. Specifically, classification accuracy increased for two classes — Erect dwarf-shrub tundra with 6% and Fresh Water with 10%. The classification accuracy as well test sites were analyzed using in situ data collected during three fieldwork campaigns in August-September (2016–2018) in the surrounding of Bovanenkovo settlement.

Original languageEnglish
Title of host publicationSDM-2021 Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021
Subtitle of host publicationProceedings of the All-Russian Conference With International Participation "Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes" (SDM-2021) Novosibirsk, Russia, August 24-27, 2021
EditorsYurii I. Shokin, Victor V. Alt, Igor V. Bychkov, Oleg I. Potaturkin, Igor A. Pestunov
PublisherCEUR-WS.org
Pages330-342
Number of pages13
Publication statusPublished - 2021
Event2021 All-Russian Conference with International Participation "Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes", SDM 2021 - Novosibirsk, Russian Federation
Duration: 24 Aug 202127 Aug 2021

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR-ws
Volume3006
ISSN (Print)1613-0073

Conference

Conference2021 All-Russian Conference with International Participation "Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes", SDM 2021
Country/TerritoryRussian Federation
CityNovosibirsk
Period24/08/2127/08/21

Bibliographical note

Funding Information:
This study was carried out as a part of State Task (Projects 0306-2021-0007, 121031200178-8) of the Institute for Water and Environmental Problems SB RAS with the financial support of the Non-Profit Partnership “Russian Center for Arctic Development” (Salekhard).

Publisher Copyright:
© 2021 Copyright for this paper by its authors.

Keywords

  • Central Yamal
  • Classification
  • Contextual analysis
  • Maximum likelihood
  • Sentinel-1
  • Sentinel-2
  • Vegetation

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