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A method for detecting plastic waste floating using Sentinel 2 high spatial resolution image: a case study in the coastal area of Vietnam
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This study used Sentinel-2 high-resolution satellite imagery to detect and classify floating plastic waste in coastal waters of Vietnam. A spectral differentiation approach successfully identified plastic mesh in shallow coastal areas, demonstrating remote sensing as a viable tool for ocean plastic waste monitoring.
Ocean plastic waste pollution is now becoming a serious environmental problem, especially for a country with a long coastline and wide sea like Vietnam. The remote sensing method is considered suitable and effective in early detection and classification of ocean plastic waste due to the difference in spectral reflectance of plastic waste compared to the surrounding sea. This paper presents the results of identification and classification of plastic mesh in coastal areas of Vietnam by using Sentinel 2 MSI high spatial resolution optical images. First, water was extracted from Sentinel 2 image by thresholding method on a near-infrared band. Then, the plastic mesh was identified and classified based on Float Debris Index (FDI) index using Otsu thresholding algorithm. In the study, spectral indices such as NDVI, NDWI were also used to improve the accuracy in classifying plastic mesh. In the study, Google high spatial resolution satellite images were also used to evaluate the accuracy of plastic mesh classification. The obtained results show that, in 02 test areas, the proposed method allows detecting plastic mesh with an accuracy of over 90 %. The results obtained in the study can be used to provide input information for models of forecasting and assessing the impact of ocean plastic waste pollution on coastal environments.
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