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Marine plastic pollution detection and identification by using remote sensing-meta analysis.
Waqas, Muhammad; Wong, Man Sing; Stocchino, Alessandro; Abbas, Sawaid; Hafeez, Sidrah; Zhu, Rui.
Afiliação
  • Waqas M; Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
  • Wong MS; Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China; Research Institute of Land and Space, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China. Electronic address: Ls.charles@polyu.edu.hk.
  • Stocchino A; Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
  • Abbas S; Remote Sensing, GIS and Climatic Research Lab (RSGCRL), National Center of GIS and Space Applications, University of the Punjab, Lahore 54590, Pakistan.
  • Hafeez S; Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
  • Zhu R; Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China; Research Institute of Land and Space, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
Mar Pollut Bull ; 197: 115746, 2023 Dec.
Article em En | MEDLINE | ID: mdl-37951122
ABSTRACT
The persistent plastic litter, originating from different sources and transported from rivers to oceans, has posed serious biological, ecological, and chemical effects on the marine ecosystem, and is considered a global issue. In the past decade, many studies have identified, monitored, and tracked marine plastic debris in coastal and open ocean areas using remote sensing technologies. Compared to traditional surveying methods, high-resolution (spatial and temporal) multispectral or hyperspectral remote sensing data have been substantially used to monitor floating marine macro litter (FMML). In this systematic review, we present an overview of remote sensing data and techniques for detecting FMML, as well as their challenges and opportunities. We reviewed the studies based on different sensors and platforms, spatial and spectral resolution, ground sampling data, plastic detection methods, and accuracy obtained in detecting marine litter. In addition, this study elaborates the usefulness of high-resolution remote sensing data in Visible (VIS), Near-infrared (NIR), and Short-Wave InfraRed (SWIR) range, along with spectral signatures of plastic, in-situ samples, and spectral indices for automatic detection of FMML. Moreover, the Thermal Infrared (TIR), Synthetic aperture radar (SAR), and Light Detection and Ranging (LiDAR) data were introduced and these were demonstrated that could be used as a supplement dataset for the identification and quantification of FMML.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Tecnologia de Sensoriamento Remoto Tipo de estudo: Systematic_reviews Idioma: En Revista: Mar Pollut Bull Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Tecnologia de Sensoriamento Remoto Tipo de estudo: Systematic_reviews Idioma: En Revista: Mar Pollut Bull Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China