Abstract
Coastal management has a critical role in estimating the coastal environmental and socio-economic dynamics, providing various vital regional and local services. Remote sensing earth observations are essential for detecting and monitoring shorelines. UAVs combined with satellite remote sensing address the shoreline delineation problems to detect the shoreline and identify the shoreline zones. The paper presents a shoreline delineation service utilizing UAV and Sentinel 2 images within a Data Cube environment for monitoring coastal areas. The BandRatio, McFeeters, MNDWI1, and MNDWI2 algorithms have been implemented in the service to analyze the accuracy of each algorithm by comparing satellite and UAV-derived shorelines. As a case study, the Lake Sevan shoreline delineation, as one of the most incredible freshwater lakes in Eurasia, has been studied using the service. MNDWI2 algorithm showed the best accuracy for Lake Sevan shoreline delineation.
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Acknowledgements
The research was supported by the University of Geneva Leading House and the State Committee of Science of the Republic of Armenia by the projects entitled “ADC4SD: Armenian Data Cube for Sustainable Development”, “Self-organized Swarm of UAVs Smart Cloud Platform Equipped with Multi-agent Algorithms and Systems” (Nr. 21AG-1B052) and “Remote sensing data processing methods using neural networks and deep learning to predict changes in weather phenomena” (Nr. 21SC-BRFFR-1B009).
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Communicated by: H. Babaie
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Astsatryan, H., Grigoryan, H., Abrahamyan, R. et al. Shoreline delineation service: using an earth observation data cube and sentinel 2 images for coastal monitoring. Earth Sci Inform 15, 1587–1596 (2022). https://doi.org/10.1007/s12145-022-00806-7
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DOI: https://doi.org/10.1007/s12145-022-00806-7