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

• Main Authors: Plutalova, Tatiana G., Teshebaeva, Kanayim, Balykin, Dmitry N., Puzanov, Alexander V., van Huissteden, Jacobus, Koveshnikov, Mikhail I., Lovtskaya, Olga V., Kovalevskaya, Nelly M.
• Other Authors: Shokin, Yurii I., Alt, Victor V., Bychkov, Igor V., Potaturkin, Oleg I., Pestunov, Igor A.
• Format: Article in Journal/Newspaper
• Language: English
• Published: CEUR-WS.org 2021
• Subjects: Central Yamal; Classification; Contextual analysis; Maximum likelihood; Sentinel-1; Sentinel-2; Vegetation; Arctic; Bovanenkovo; Tundra; Siberia
• 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

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.