Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery
| Autor: | 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. |
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| Přispěvatelé: | Earth and Climate |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | 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, 330-342 STARTPAGE=330;ENDPAGE=342;TITLE=SDM-2021 Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021 |
| 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 |
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