Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery
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...
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Language: | English |
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CEUR-WS.org
2021
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Online Access: | https://research.vu.nl/en/publications/3ba5b8f2-5f99-4764-9e64-cf0fe82c67c3 https://hdl.handle.net/1871.1/3ba5b8f2-5f99-4764-9e64-cf0fe82c67c3 http://www.scopus.com/inward/record.url?scp=85120972195&partnerID=8YFLogxK http://www.scopus.com/inward/citedby.url?scp=85120972195&partnerID=8YFLogxK http://ceur-ws.org/Vol-3006/39_regular_paper.pdf |
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ftvuamstcris:oai:research.vu.nl:publications/3ba5b8f2-5f99-4764-9e64-cf0fe82c67c3 2024-06-23T07:50:21+00:00 Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery Plutalova, Tatiana G. Teshebaeva, Kanayim Balykin, Dmitry N. Puzanov, Alexander V. van Huissteden, Jacobus Koveshnikov, Mikhail I. Lovtskaya, Olga V. Kovalevskaya, Nelly M. Shokin, Yurii I. Alt, Victor V. Bychkov, Igor V. Potaturkin, Oleg I. Pestunov, Igor A. 2021 https://research.vu.nl/en/publications/3ba5b8f2-5f99-4764-9e64-cf0fe82c67c3 https://hdl.handle.net/1871.1/3ba5b8f2-5f99-4764-9e64-cf0fe82c67c3 http://www.scopus.com/inward/record.url?scp=85120972195&partnerID=8YFLogxK http://www.scopus.com/inward/citedby.url?scp=85120972195&partnerID=8YFLogxK http://ceur-ws.org/Vol-3006/39_regular_paper.pdf eng eng CEUR-WS.org https://research.vu.nl/en/publications/3ba5b8f2-5f99-4764-9e64-cf0fe82c67c3 info:eu-repo/semantics/openAccess 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 . 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 Classification Contextual analysis Maximum likelihood Sentinel-1 Sentinel-2 Vegetation contributionToPeriodical 2021 ftvuamstcris 2024-06-06T00:28:07Z 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. Article in Journal/Newspaper Arctic Tundra Siberia Vrije Universiteit Amsterdam (VU): Research Portal Arctic Bovanenkovo ENVELOPE(68.437,68.437,70.354,70.354) |
institution |
Open Polar |
collection |
Vrije Universiteit Amsterdam (VU): Research Portal |
op_collection_id |
ftvuamstcris |
language |
English |
topic |
Central Yamal Classification Contextual analysis Maximum likelihood Sentinel-1 Sentinel-2 Vegetation |
spellingShingle |
Central Yamal Classification Contextual analysis Maximum likelihood Sentinel-1 Sentinel-2 Vegetation Plutalova, Tatiana G. Teshebaeva, Kanayim Balykin, Dmitry N. Puzanov, Alexander V. van Huissteden, Jacobus Koveshnikov, Mikhail I. Lovtskaya, Olga V. Kovalevskaya, Nelly M. Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery |
topic_facet |
Central Yamal Classification Contextual analysis Maximum likelihood Sentinel-1 Sentinel-2 Vegetation |
description |
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. |
author2 |
Shokin, Yurii I. Alt, Victor V. Bychkov, Igor V. Potaturkin, Oleg I. Pestunov, Igor A. |
format |
Article in Journal/Newspaper |
author |
Plutalova, Tatiana G. Teshebaeva, Kanayim Balykin, Dmitry N. Puzanov, Alexander V. van Huissteden, Jacobus Koveshnikov, Mikhail I. Lovtskaya, Olga V. Kovalevskaya, Nelly M. |
author_facet |
Plutalova, Tatiana G. Teshebaeva, Kanayim Balykin, Dmitry N. Puzanov, Alexander V. van Huissteden, Jacobus Koveshnikov, Mikhail I. Lovtskaya, Olga V. Kovalevskaya, Nelly M. |
author_sort |
Plutalova, Tatiana G. |
title |
Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery |
title_short |
Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery |
title_full |
Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery |
title_fullStr |
Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery |
title_full_unstemmed |
Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery |
title_sort |
central yamal vegetation monitoring based on sentinel-2 and sentinel-1 imagery |
publisher |
CEUR-WS.org |
publishDate |
2021 |
url |
https://research.vu.nl/en/publications/3ba5b8f2-5f99-4764-9e64-cf0fe82c67c3 https://hdl.handle.net/1871.1/3ba5b8f2-5f99-4764-9e64-cf0fe82c67c3 http://www.scopus.com/inward/record.url?scp=85120972195&partnerID=8YFLogxK http://www.scopus.com/inward/citedby.url?scp=85120972195&partnerID=8YFLogxK http://ceur-ws.org/Vol-3006/39_regular_paper.pdf |
long_lat |
ENVELOPE(68.437,68.437,70.354,70.354) |
geographic |
Arctic Bovanenkovo |
geographic_facet |
Arctic Bovanenkovo |
genre |
Arctic Tundra Siberia |
genre_facet |
Arctic Tundra Siberia |
op_source |
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 . 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 > |
op_relation |
https://research.vu.nl/en/publications/3ba5b8f2-5f99-4764-9e64-cf0fe82c67c3 |
op_rights |
info:eu-repo/semantics/openAccess |
_version_ |
1802641223166459904 |