Airborne Spectral Reflectance Dataset of Submerged Plastic Targets in a Coastal Environment

Apostolos Papakonstantinou (), Argyrios Moustakas, Polychronis Kolokoussis, Dimitris Papageorgiou, Robin de Vries and Konstantinos Topouzelis
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Apostolos Papakonstantinou: Department of Marine Sciences, University of the Aegean, University Hill, 81100 Mytilene, Greece
Argyrios Moustakas: Department of Marine Sciences, University of the Aegean, University Hill, 81100 Mytilene, Greece
Polychronis Kolokoussis: School of Rural, Surveying and Geoinformatics Engineering, National Technical University, 15780 Athens, Greece
Dimitris Papageorgiou: Department of Marine Sciences, University of the Aegean, University Hill, 81100 Mytilene, Greece
Robin de Vries: The Ocean Cleanup, Batavierenstraat 15, 3014 JH Rotterdam, The Netherlands
Konstantinos Topouzelis: Department of Marine Sciences, University of the Aegean, University Hill, 81100 Mytilene, Greece

Data, 2023, vol. 8, issue 1, 1-13

Abstract: Among the emerging applications of remote sensing technologies, the remote detection of plastic litter has observed successful applications in recent years. However, while the number of studies and datasets for spectral characterization of plastic is growing, few studies address plastic litter while being submerged in natural seawater in an outdoor context. This study aims to investigate the feasibility of hyperspectral characterization of submerged plastic litter in less-than-ideal conditions. We present a hyperspectral dataset of eight different polymers in field conditions, taken by an unmanned aerial vehicle (UAV) on different days in a three-week period. The measurements were carried out off the coast of Mytilene, Greece. The team collected the dataset using a Bayspec OCI-F push broom sensor from 25 m and 40 m height above the water. For a contextual background, the dataset also contains optical (RGB) high-resolution orthomosaics.

Keywords: hyperspectral data; spectral reflectances; plastic targets; UAV Hyperspectral (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2023
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