Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic Indexes

Hyperspectral PRISMA images are new and have not yet been evaluated for their ability to detect marine plastic litter. The hyperspectral PRISMA images have a fine spectral resolution, however, their spatial resolution is not high enough to enable the discrimination of small plastic objects in the oc...

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Main Authors: Maria Kremezi, Viktoria Kristollari, Vassilia Karathanassi, Konstantinos Topouzelis, Pol Kolokoussis, Nicolo Taggio, Antonello Aiello, Giulio Ceriola, Enrico Barbone, Paolo Corradi
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9406795/
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spelling doaj-c30a72a3a3b04e82b029304aa65fa27e2021-04-28T23:00:55ZengIEEEIEEE Access2169-35362021-01-019619556197110.1109/ACCESS.2021.30739039406795Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic IndexesMaria Kremezi0https://orcid.org/0000-0002-1579-3520Viktoria Kristollari1https://orcid.org/0000-0001-5112-4079Vassilia Karathanassi2https://orcid.org/0000-0002-8834-4734Konstantinos Topouzelis3https://orcid.org/0000-0002-1916-1600Pol Kolokoussis4https://orcid.org/0000-0002-5420-0900Nicolo Taggio5Antonello Aiello6https://orcid.org/0000-0003-4446-0191Giulio Ceriola7Enrico Barbone8Paolo Corradi9Laboratory of Remote Sensing, School of Rural and Surveying Engineering, National Technical University of Athens, Zografou, GreeceLaboratory of Remote Sensing, School of Rural and Surveying Engineering, National Technical University of Athens, Zografou, GreeceLaboratory of Remote Sensing, School of Rural and Surveying Engineering, National Technical University of Athens, Zografou, GreeceDepartment of Marine Sciences, University of the Aegean, Mytilene, GreeceLaboratory of Remote Sensing, School of Rural and Surveying Engineering, National Technical University of Athens, Zografou, GreecePlanetek Italia s.r.l., Bari, ItalyPlanetek Italia s.r.l., Bari, ItalyPlanetek Italia s.r.l., Bari, ItalyRegional Agency for the Prevention and Protection of the Environment (ARPA Puglia), Bari, ItalyMechatronics and Optics Division, Optics Section, European Space Research and Technology Centre (ESTEC), European Space Agency, Noordwijk, The NetherlandsHyperspectral PRISMA images are new and have not yet been evaluated for their ability to detect marine plastic litter. The hyperspectral PRISMA images have a fine spectral resolution, however, their spatial resolution is not high enough to enable the discrimination of small plastic objects in the ocean. Pansharpening with the panchromatic data enhances their spatial resolution and makes their detection capabilities a technological challenge. This study exploits, for the first time, the potential of using satellite hyperspectral data in detecting small-sized marine plastic litter. Controlled experiments with plastic targets of various sizes constructed from several materials have been conducted. The required pre-processing steps have been defined and 13 pansharpening methods have been applied and evaluated for their ability to spectrally discriminate plastics from water. Among them, the PCA-based substitution efficiently separates plastic spectra from water without producing duplicate edges, or pixelation. Plastic targets with size equivalent to 8% of the original hyperspectral image pixel coverage are easily detected. The same targets can also be observed in the panchromatic image, however, they cannot be detected solely by the panchromatic information as they are confused with other appearances. Exploiting spectra derived from the pan-sharpened hyperspectral images, an index combining methodology has been developed, which enables the detection of plastic objects. Although spectra of plastic materials present similarities with water spectra, some spectral characteristics can be utilized for producing marine plastic litter indexes. Based on these indexes, the index combining methodology has successfully detected the plastic targets and differentiated them from other materials.https://ieeexplore.ieee.org/document/9406795/PRISMA satellite datahyperspectral imagingpansharpeningmarine pollutionplastic litter detectionindexes
collection DOAJ
language English
format Article
sources DOAJ
author Maria Kremezi
Viktoria Kristollari
Vassilia Karathanassi
Konstantinos Topouzelis
Pol Kolokoussis
Nicolo Taggio
Antonello Aiello
Giulio Ceriola
Enrico Barbone
Paolo Corradi
spellingShingle Maria Kremezi
Viktoria Kristollari
Vassilia Karathanassi
Konstantinos Topouzelis
Pol Kolokoussis
Nicolo Taggio
Antonello Aiello
Giulio Ceriola
Enrico Barbone
Paolo Corradi
Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic Indexes
IEEE Access
PRISMA satellite data
hyperspectral imaging
pansharpening
marine pollution
plastic litter detection
indexes
author_facet Maria Kremezi
Viktoria Kristollari
Vassilia Karathanassi
Konstantinos Topouzelis
Pol Kolokoussis
Nicolo Taggio
Antonello Aiello
Giulio Ceriola
Enrico Barbone
Paolo Corradi
author_sort Maria Kremezi
title Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic Indexes
title_short Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic Indexes
title_full Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic Indexes
title_fullStr Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic Indexes
title_full_unstemmed Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic Indexes
title_sort pansharpening prisma data for marine plastic litter detection using plastic indexes
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2021-01-01
description Hyperspectral PRISMA images are new and have not yet been evaluated for their ability to detect marine plastic litter. The hyperspectral PRISMA images have a fine spectral resolution, however, their spatial resolution is not high enough to enable the discrimination of small plastic objects in the ocean. Pansharpening with the panchromatic data enhances their spatial resolution and makes their detection capabilities a technological challenge. This study exploits, for the first time, the potential of using satellite hyperspectral data in detecting small-sized marine plastic litter. Controlled experiments with plastic targets of various sizes constructed from several materials have been conducted. The required pre-processing steps have been defined and 13 pansharpening methods have been applied and evaluated for their ability to spectrally discriminate plastics from water. Among them, the PCA-based substitution efficiently separates plastic spectra from water without producing duplicate edges, or pixelation. Plastic targets with size equivalent to 8% of the original hyperspectral image pixel coverage are easily detected. The same targets can also be observed in the panchromatic image, however, they cannot be detected solely by the panchromatic information as they are confused with other appearances. Exploiting spectra derived from the pan-sharpened hyperspectral images, an index combining methodology has been developed, which enables the detection of plastic objects. Although spectra of plastic materials present similarities with water spectra, some spectral characteristics can be utilized for producing marine plastic litter indexes. Based on these indexes, the index combining methodology has successfully detected the plastic targets and differentiated them from other materials.
topic PRISMA satellite data
hyperspectral imaging
pansharpening
marine pollution
plastic litter detection
indexes
url https://ieeexplore.ieee.org/document/9406795/
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