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

Autor:	Plutalova, Tatiana G., Kanayim Teshebaeva, Balykin, Dmitry N., Puzanov, Alexander V., Jacobus van Huissteden, Koveshnikov, Mikhail I., Lovtskaya, Olga V., Kovalevskaya, Nelly M.
Přispěvatelé:	Shokin, Yurii I., Alt, Victor V., Bychkov, Igor V., Potaturkin, Oleg I., Pestunov, Igor A.
Předmět:	Vegetation Contextual analysis Sentinel-1 Central Yamal Sentinel-2 Classification Maximum likelihood
Zdroj:	Vrije Universiteit Amsterdam 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 >
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::4d5c5255a35fad8755e01d229997746c https://research.vu.nl/en/publications/3ba5b8f2-5f99-4764-9e64-cf0fe82c67c3 Zobrazit plný text záznamu