Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/29159
Title: INTEGRATED MONITORING SYSTEM FOR BEACH LITTER PREPAREDNESS AND RESPONSE
Authors: Topouzelis, Konstantinos 
Papakonstantinou, Apostolos 
Batsaris, Marios 
Spondylidis, Spyros 
Major Field of Science: Engineering and Technology
Field Category: Civil Engineering
Keywords: Marine litter;AI;Drone;Coastal area
Issue Date: 1-Jan-2021
Source: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 11-16 July 2021
Conference: International Geoscience and Remote Sensing Symposium (IGARSS) 
Abstract: The detection of the coastal and Marine Litter (ML) using UAS data in combination with machine learning methods is an important step towards an automated process of detecting and mapping ML concentrations. The Visual Geometry Group-19 (VGG19) CNN architecture is used to classify UAS image tiles in two classes; litter and no litter. Testing the geographical transferability of our method to an unseen dataset, we found that the VVG19 CNN obtained an overall accuracy of 83.67 % and an F-score of 81.63%. The produced ML density maps can be used as a decision-making support tool. The integration and visualization of the marine litter and density information facilitate decision-making by all related to the problem stakeholders and decision-makers.
URI: https://hdl.handle.net/20.500.14279/29159
ISBN: 9781665403696
DOI: 10.1109/IGARSS47720.2021.9553443
Type: Conference Papers
Affiliation : University of the Aegean 
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