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Floodplain Forest Mapping with Sentinel-2 Imagery: Case Study of Naryn River, Kyrgyzstan

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Abstract

The article presents the results of studies on the use of Sentinel-2 satellite data and the application of SNAP and ArcGIS software for the classification and mapping of forest cover of the Naryn river floodplain. Available inventory maps of the Kyrgyz Forestry Administration are outdated and do not meet the current requirements and need to be updated with the use of satellite images from different systems. High-resolution Sentinel-2A multispectral imagery has been used to study the supervised forest cover classification of the floodplain areas of the Naryn River in Kyrgyzstan for contributing to forest inventory and general analysis of the floodplain forest ecosystems. Using such high-resolution images in this study was due to the peculiar properties of classification and mapping of small vegetation areas of the unstable floodplains of mountain rivers. Supervised classification was performed using S2A MSI and WorldView-2 satellite images through SNAP software and field investigation data. Level-1C S2A multispectral images are processed to the Level-2A using Sen2Cor for the atmospheric corrections and further classification. The research results show the usefulness of high-resolution Sentinel-2 imagery for land use and land cover classification as well as the best freely available tool for thematic mapping of riparian forests.

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Acknowledgments

This study is part of the project Ecosystem Assessment and Capacity Building along the Central Asian Rivers Tarim and Naryn funded by the Volkswagen Foundation. The authors would like to thank the European Space Agency (ESA) for the provision of Sentinel-2A data and Sentinel Application Platform.

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Correspondence to Akylbek Chymyrov .

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Chymyrov, A., Betz, F., Baibagyshov, E., Kurban, A., Cyffka, B., Halik, U. (2018). Floodplain Forest Mapping with Sentinel-2 Imagery: Case Study of Naryn River, Kyrgyzstan. In: Egamberdieva, D., Öztürk, M. (eds) Vegetation of Central Asia and Environs. Springer, Cham. https://doi.org/10.1007/978-3-319-99728-5_14

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