Monitoring of Plastic Islands in River Environment Using Sentinel-1 SAR Data

Abstract

Plastics in the river environment are of major concern due to their potential pathways into the ocean, their persistence in the environment, and their impacts on human and marine health. It has been documented that plastic concentrations in riparian environments are higher following major rain events, where plastic can be moved through surface runoff. Considering the hazard that plastic waste poses to the environment, monitoring techniques are needed to aid in locating, monitoring, and remediating plastic waste within these systems. Dams are known to trap sediments and pollutants, such as metals and Polychlorinated Biphenyls (PCBs). While there is an established background on the monitoring of dams using the synoptic coverage provided by satellite imaging to observe water quality and volume, the detection of marine debris in riparian systems remains challenging, especially in cloudy conditions. Herein, we exploit the use of Synthetic Aperture Radar (SAR) to understand its capabilities for monitoring marine debris. This research focuses on detecting plastic islands within the Drina River system in Bosnia and Herzegovina and Serbia. Here, the results show that the monitoring of these plastic accumulations is feasible using Sentinel-1 SAR data. A quantitative analysis of detection performance is presented using traditional and state-of-the-art change detectors. The analysis of these detectors indicates that detectors that can utilise the coherent data from Single Look Complex (SLC) acquisitions are perform better when compared with those that only utilise incoherent data from Ground Range-Detected (GRD) acquisitions, with true positive detection ratings of ~95% with 0.1% false alarm rates seen in the best-performing detector. We also found that that the cross-pol VH channel provides better detection than those based on single-pol VV polarisation.

Emerging Technologies for Remote Sensing of Floating and Submerged Plastic Litter

“…Simpson et al [117] used Sentinel 1 images to detect large debris accumulations near dams. Dams are known to trap sediments as well as pollutants, such as plastic and metal.…”

Riverine Microplastic Quantification: A Novel Approach Integrating Satellite Images, Neural Network, and Suspended Sediment Data as a Proxy

“…The images covered the longitudinal sites in August 2021 (eight images) and July 2022 (seven images), and the temporal measurements at Mindszent (March 2021-December 2022; 128 images) and Szeged (March 2021-March 2022; 70 images). The Ground Range Detected (GRD) Level 1 data with the Interferometric Wide Swath (IW) mode were employed since it is commonly used in water bodies' backscattering investigations [14]. The spatial resolution of the images is 10 m, acquired every 5 days in two channels [cross-(VH) and co-(VV) polarization].…”

“…Alternatively, we hypothesized that SAR images could directly estimate MPC. Particularly, because He et al [13] stated that the water dielectric constant is associated with the particulate material concentration and SAR images are highly sensitive to dielectric variations [14]. Therefore, our study aims to evaluate their direct correlation.…”