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Quantification of floating riverine macro-debris transport using an image processing approach

A new algorithm has been developed to quantify floating macro-debris transport on river surfaces that consists of three fundamental techniques: (1) generating a difference image of the colour difference between the debris and surrounding water in the CIELuv colour space, (2) detecting the debris pix...

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Detalles Bibliográficos
Autores principales: Kataoka, Tomoya, Nihei, Yasuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7010822/
https://www.ncbi.nlm.nih.gov/pubmed/32042032
http://dx.doi.org/10.1038/s41598-020-59201-1
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author Kataoka, Tomoya
Nihei, Yasuo
author_facet Kataoka, Tomoya
Nihei, Yasuo
author_sort Kataoka, Tomoya
collection PubMed
description A new algorithm has been developed to quantify floating macro-debris transport on river surfaces that consists of three fundamental techniques: (1) generating a difference image of the colour difference between the debris and surrounding water in the CIELuv colour space, (2) detecting the debris pixels from the difference image, and (3) calculating the debris area flux via the template matching method. Debris pixels were accurately detected from the images taken of the laboratory channel and river water surfaces and were consistent with those detected by visual observation. The area fluxes were statistically significantly correlated with the mass fluxes measured through debris collection. The mass fluxes calculated by multiplying the area fluxes with the debris mass per unit area (M/A) were significantly related to the flood rising stage flow rates and agreed with the mass fluxes measured through debris collection. In our algorithm, plastic mass fluxes can be estimated via calibration using the mass percentage of plastics to the total debris in target rivers. Quantifying riverine macro-plastic transport is essential to formulating countermeasures, mitigating adverse plastic pollution impacts and understanding global-scale riverine macro-plastic transport.
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spelling pubmed-70108222020-02-21 Quantification of floating riverine macro-debris transport using an image processing approach Kataoka, Tomoya Nihei, Yasuo Sci Rep Article A new algorithm has been developed to quantify floating macro-debris transport on river surfaces that consists of three fundamental techniques: (1) generating a difference image of the colour difference between the debris and surrounding water in the CIELuv colour space, (2) detecting the debris pixels from the difference image, and (3) calculating the debris area flux via the template matching method. Debris pixels were accurately detected from the images taken of the laboratory channel and river water surfaces and were consistent with those detected by visual observation. The area fluxes were statistically significantly correlated with the mass fluxes measured through debris collection. The mass fluxes calculated by multiplying the area fluxes with the debris mass per unit area (M/A) were significantly related to the flood rising stage flow rates and agreed with the mass fluxes measured through debris collection. In our algorithm, plastic mass fluxes can be estimated via calibration using the mass percentage of plastics to the total debris in target rivers. Quantifying riverine macro-plastic transport is essential to formulating countermeasures, mitigating adverse plastic pollution impacts and understanding global-scale riverine macro-plastic transport. Nature Publishing Group UK 2020-02-10 /pmc/articles/PMC7010822/ /pubmed/32042032 http://dx.doi.org/10.1038/s41598-020-59201-1 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Kataoka, Tomoya
Nihei, Yasuo
Quantification of floating riverine macro-debris transport using an image processing approach
title Quantification of floating riverine macro-debris transport using an image processing approach
title_full Quantification of floating riverine macro-debris transport using an image processing approach
title_fullStr Quantification of floating riverine macro-debris transport using an image processing approach
title_full_unstemmed Quantification of floating riverine macro-debris transport using an image processing approach
title_short Quantification of floating riverine macro-debris transport using an image processing approach
title_sort quantification of floating riverine macro-debris transport using an image processing approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7010822/
https://www.ncbi.nlm.nih.gov/pubmed/32042032
http://dx.doi.org/10.1038/s41598-020-59201-1
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