Marine plastic pollution detection and identification by using remote sensing-meta analysis.

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.