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

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

Earth and Climate

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-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 language	English
Title of host publication	SDM-2021 Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021
Subtitle of host publication	Proceedings 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
Editors	Yurii I. Shokin, Victor V. Alt, Igor V. Bychkov, Oleg I. Potaturkin, Igor A. Pestunov
Publisher	CEUR-WS.org
Pages	330-342
Number of pages	13
Publication status	Published - 2021
Event	2021 All-Russian Conference with International Participation "Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes", SDM 2021 - Novosibirsk, Russian Federation Duration: 24 Aug 2021 → 27 Aug 2021

Publication series

Name	CEUR Workshop Proceedings
Publisher	CEUR-ws
Volume	3006
ISSN (Print)	1613-0073

Conference

Conference	2021 All-Russian Conference with International Participation "Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes", SDM 2021
Country/Territory	Russian Federation
City	Novosibirsk
Period	24/08/21 → 27/08/21

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.

Funding

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).

Keywords

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

Access to Document

http://ceur-ws.org/Vol-3006/39_regular_paper.pdf

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Plutalova, T. G., Teshebaeva, K., Balykin, D. N., Puzanov, A. V., van Huissteden, J., Koveshnikov, M. I., Lovtskaya, O. V., & Kovalevskaya, N. M. (2021). Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery. In Y. I. Shokin, V. V. Alt, I. V. Bychkov, O. I. Potaturkin, & I. A. Pestunov (Eds.), SDM-2021 Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021: Proceedings 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 (pp. 330-342). (CEUR Workshop Proceedings; Vol. 3006). CEUR-WS.org. http://ceur-ws.org/Vol-3006/39_regular_paper.pdf

Plutalova, Tatiana G. ; Teshebaeva, Kanayim ; Balykin, Dmitry N. et al. / Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery. SDM-2021 Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021: Proceedings 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. editor / Yurii I. Shokin ; Victor V. Alt ; Igor V. Bychkov ; Oleg I. Potaturkin ; Igor A. Pestunov. CEUR-WS.org, 2021. pp. 330-342 (CEUR Workshop Proceedings).

@inproceedings{3ba5b8f25f9947649e64cf0fe82c67c3,

title = "Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery",

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.",

keywords = "Central Yamal, Classification, Contextual analysis, Maximum likelihood, Sentinel-1, Sentinel-2, Vegetation",

author = "Plutalova, {Tatiana G.} and Kanayim Teshebaeva and Balykin, {Dmitry N.} and Puzanov, {Alexander V.} and {van Huissteden}, Jacobus and Koveshnikov, {Mikhail I.} and Lovtskaya, {Olga V.} and Kovalevskaya, {Nelly M.}",

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: {\textcopyright} 2021 Copyright for this paper by its authors.; 2021 All-Russian Conference with International Participation {"}Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes{"}, SDM 2021 ; Conference date: 24-08-2021 Through 27-08-2021",

year = "2021",

language = "English",

series = "CEUR Workshop Proceedings",

publisher = "CEUR-WS.org",

pages = "330--342",

editor = "Shokin, {Yurii I.} and Alt, {Victor V.} and Bychkov, {Igor V.} and Potaturkin, {Oleg I.} and Pestunov, {Igor A.}",

booktitle = "SDM-2021 Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021",

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Plutalova, TG, Teshebaeva, K, Balykin, DN, Puzanov, AV, van Huissteden, J, Koveshnikov, MI, Lovtskaya, OV & Kovalevskaya, NM 2021, Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery. in YI Shokin, VV Alt, IV Bychkov, OI Potaturkin & IA Pestunov (eds), SDM-2021 Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021: Proceedings 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. CEUR Workshop Proceedings, vol. 3006, CEUR-WS.org, pp. 330-342, 2021 All-Russian Conference with International Participation "Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes", SDM 2021, Novosibirsk, Russian Federation, 24/08/21. <http://ceur-ws.org/Vol-3006/39_regular_paper.pdf>

Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery. / Plutalova, Tatiana G.; Teshebaeva, Kanayim; Balykin, Dmitry N. et al.
SDM-2021 Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021: Proceedings 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. ed. / Yurii I. Shokin; Victor V. Alt; Igor V. Bychkov; Oleg I. Potaturkin; Igor A. Pestunov. CEUR-WS.org, 2021. p. 330-342 (CEUR Workshop Proceedings; Vol. 3006).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery

AU - Plutalova, Tatiana G.

AU - Teshebaeva, Kanayim

AU - Balykin, Dmitry N.

AU - Puzanov, Alexander V.

AU - van Huissteden, Jacobus

AU - Koveshnikov, Mikhail I.

AU - Lovtskaya, Olga V.

AU - Kovalevskaya, Nelly M.

N1 - 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.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - Central Yamal

KW - Classification

KW - Contextual analysis

KW - Maximum likelihood

KW - Sentinel-1

KW - Sentinel-2

KW - Vegetation

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M3 - Conference contribution

AN - SCOPUS:85120972195

T3 - CEUR Workshop Proceedings

SP - 330

EP - 342

BT - SDM-2021 Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021

A2 - Shokin, Yurii I.

A2 - Alt, Victor V.

A2 - Bychkov, Igor V.

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A2 - Pestunov, Igor A.

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ER -

Plutalova TG, Teshebaeva K, Balykin DN, Puzanov AV, van Huissteden J, Koveshnikov MI et al. Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery. In Shokin YI, Alt VV, Bychkov IV, Potaturkin OI, Pestunov IA, editors, SDM-2021 Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021: Proceedings 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. CEUR-WS.org. 2021. p. 330-342. (CEUR Workshop Proceedings). Epub 2021 Nov 12.

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

Abstract

Publication series

Conference

Bibliographical note

Funding

Keywords

Access to Document

Persistent URL (handle)

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