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

Area of Science:

• Environmental Science
• Remote Sensing Technology
• Marine Biology

Background:

• Marine plastic litter poses significant biological, ecological, and chemical threats to marine ecosystems globally.
• Remote sensing technologies have become crucial for identifying, monitoring, and tracking marine plastic debris in various ocean areas.
• High-resolution multispectral and hyperspectral remote sensing data are increasingly utilized for monitoring floating marine macro litter (FMML).

Approach:

• This systematic review provides an overview of remote sensing data and techniques for FMML detection.
• Studies were analyzed based on sensors, platforms, resolution, ground sampling, detection methods, and accuracy.
• The review elaborates on the utility of Visible (VIS), Near-infrared (NIR), and Short-Wave InfraRed (SWIR) data, spectral signatures, and indices for automatic FMML detection.

Key Points:

• High-resolution remote sensing, particularly in VIS, NIR, and SWIR ranges, is vital for detecting FMML.
• Spectral signatures of plastics and spectral indices aid in the automatic identification of floating marine litter.
• Thermal Infrared (TIR), Synthetic Aperture Radar (SAR), and Light Detection and Ranging (LiDAR) offer supplementary data for FMML identification and quantification.

Conclusions:

• Remote sensing offers advanced capabilities for monitoring and managing marine plastic pollution.
• Further research into diverse remote sensing datasets and integrated approaches can enhance FMML detection and quantification.
• Optimizing remote sensing techniques is essential for mitigating the global impact of marine plastic debris.