Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/29203
Title: Seagrass mapping in Cyprus area of interest with pixel-based image analysis
Authors: Makri, Despina 
Melillos, George 
Kalogirou, Eleftheria 
Hadjimitsis, Diofantos G. 
Keywords: Seagrass;Cyprus;Pixel-based Classification;Sentinel-2,
Issue Date: 2-May-2023
Abstract: Seagrasses are one of the most valuable ecosystems in the sea. Seagrasses provide shelter and protection to newborn fish, and food, it is an indicator of the health of coastal ecosystems and plays a key role in the protection of erosion. Seagrasses provide many ecosystem services. In order to act helpfully for the health of this kind of valuable ecosystem, it is very important to map the seagrass beds. Seagrass mapping allows us to detect, monitor, and finally protect them from different sources of pressure. Seagrasses are very sensitive to changes, and this can affect the health of this type of ecosystem. For the first step, we have to detect what exists in Cyprus's area of interest. There are many ways we can implement the detection and mapping of seagrass. We will provide an estimation with pixel-based image analysis. The purpose of the paper proceedings is to detect seagrass with pixel-based image analysis, in Cyprus's area of interest, and especially the broader area of Paphos district.
URI: https://hdl.handle.net/20.500.14279/29203
Type: Conference Papers
Affiliation : ERATOSTHENES Centre of Excellence 
Cyprus University of Technology 
Funding: The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology.”
Appears in Collections:EXCELSIOR H2020 Teaming Project Publications

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