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...
Main Authors: | , , , , , , , |
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Other Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
CEUR-WS.org
2021
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Subjects: | |
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 |
Summary: | 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. |
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