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Identification of Emergent and Floating Aquatic Vegetation Using an Unsupervised Thresholding Approach: A Case Study of the Dniester Delta in Ukraine

Topics: Earth Observation and Satellite Data; Ecological and Environmental Management; Hydrological Remote Sensing; Image Processing and Pattern Recognition; Land Management; Natural Phenomena Data Acquisition; Natural Resource Management; Spatial Data Quality and Uncertainty; Spatio-Temporal Data Acquisition; Topological Modeling and Analysis; Urban and Regional Planning; Water Information Systems

Authors: Ioannis Manakos 1 ; Eleftherios Katsikis 1 ; Sergiy Medinets 2 ; Yevgen Gazyetov 2 ; Leonidas Alagialoglou 1 and Volodymyr Medinets 2

Affiliations: 1 Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece ; 2 Odesa National I.I. Mechnikov University, Odesa, Ukraine

Keyword(s): Wetland, Sentinel-2, Floating Vegetation, Emergent Vegetation, Thresholding, Multi-Class Segmentation.

Abstract: Monitoring of emergent and floating vegetation in freshwater ecosystems is of high importance for water management in an area. This study proposes a methodology for the automatic monitoring of aquatic vegetation using indicators estimated via remote sensing image analysis. The study area is located in the Lower Dniester Basin in Southern Ukraine. The approach is developed using Sentinel-2 images and validated with field measurements. The goal is to discriminate and map three classes of aquatic surface condition; namely, areas covered with floating vegetation, or dominated by emergent vegetation, and open water. The approach is transferable across different dates over a period of three years. Results are useful for governmental authorities and natural/ national park administrations for near real-time monitoring of aquatic vegetation to mitigate the impact of overgrowth on water quality, biodiversity, and ecosystem services.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Manakos, I. ; Katsikis, E. ; Medinets, S. ; Gazyetov, Y. ; Alagialoglou, L. and Medinets, V. (2023). Identification of Emergent and Floating Aquatic Vegetation Using an Unsupervised Thresholding Approach: A Case Study of the Dniester Delta in Ukraine. In Proceedings of the 9th International Conference on Geographical Information Systems Theory, Applications and Management - GISTAM; ISBN 978-989-758-649-1; ISSN 2184-500X, SciTePress, pages 98-103. DOI: 10.5220/0012024000003473

@conference{gistam23,
author={Ioannis Manakos and Eleftherios Katsikis and Sergiy Medinets and Yevgen Gazyetov and Leonidas Alagialoglou and Volodymyr Medinets},
title={Identification of Emergent and Floating Aquatic Vegetation Using an Unsupervised Thresholding Approach: A Case Study of the Dniester Delta in Ukraine},
booktitle={Proceedings of the 9th International Conference on Geographical Information Systems Theory, Applications and Management - GISTAM},
year={2023},
pages={98-103},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012024000003473},
isbn={978-989-758-649-1},
issn={2184-500X},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Geographical Information Systems Theory, Applications and Management - GISTAM
TI - Identification of Emergent and Floating Aquatic Vegetation Using an Unsupervised Thresholding Approach: A Case Study of the Dniester Delta in Ukraine
SN - 978-989-758-649-1
IS - 2184-500X
AU - Manakos, I.
AU - Katsikis, E.
AU - Medinets, S.
AU - Gazyetov, Y.
AU - Alagialoglou, L.
AU - Medinets, V.
PY - 2023
SP - 98
EP - 103
DO - 10.5220/0012024000003473
PB - SciTePress

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