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RSS FeedsRemote Sensing, Vol. 15, Pages 1654: Investigating the Backscatter of Marine Plastic Litter Using a C- and X-band Ground Radar, during a Measurement Campaign in Deltares (Remote Sensing)

 
 

18 march 2023 14:41:47

 
Remote Sensing, Vol. 15, Pages 1654: Investigating the Backscatter of Marine Plastic Litter Using a C- and X-band Ground Radar, during a Measurement Campaign in Deltares (Remote Sensing)
 


In recent years, marine plastic pollution has seen increased coverage in the public interest and research due to a greater understanding of the scale and impact of plastic pollution within the marine environment. Considering the hazard that plastic waste poses on the environment, marine life, and on humans, remote-sensing techniques could provide timely information on their detection and dynamics. The remote sensing of marine plastic is a relatively new field and research into the capabilities of radar for detecting and monitoring marine plastic pollution is generally limited, with several interactions and mechanisms being largely unknown. Here, we exploit the use of a C- and X-band radar to understand the capabilities of monitoring marine plastics. Our results show that backscattering differences in the C- and X-band between the reference water (called here as “clean”) and the test water filled with plastic can be detected in some conditions (based on statistical analysis). Overall, the results indicate that the X-band frequency performs significantly better than the C-band frequency, with X-band detecting significant differences in backscattering in 48/68 test cases compared with C-band detecting differences in 20/67 test cases. We also find that the difference in backscattering is dependent on the size and shape of the plastic object, as well as the wave conditions which the plastic is moving on. This study provides new insights on the radar capabilities for detecting marine plastic litter and new information which can be used in the planning of future missions and studies on the remote sensing of marine plastic pollution.


 
76 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 15, Pages 1652: Prediction of the Area of High-Turbidity Water in the Yatsushiro Sea, Japan, Using Machine Learning with Satellite, Meteorological, and Oceanographic Data (Remote Sensing)
Remote Sensing, Vol. 15, Pages 1655: Prior Semantic Information Guided Change Detection Method for Bi-temporal High-Resolution Remote Sensing Images (Remote Sensing)
 
 
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