利用Sentinel 2高空间分辨率图像检测漂浮塑料垃圾的方法:以越南沿海地区为例研究

L. Trinh, V. Nghiem, Tran Xuan Bien, Van Phu Le, Sach Thanh Nguyen
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引用次数: 0

摘要

海洋塑料垃圾污染正在成为一个严重的环境问题,特别是对于像越南这样一个海岸线长、海洋宽的国家来说。由于塑料垃圾的光谱反射率与周围海域存在差异,因此认为遥感方法适用于海洋塑料垃圾的早期检测和分类。本文介绍了利用Sentinel 2 MSI高空间分辨率光学图像对越南沿海地区塑料网进行识别和分类的结果。首先,在近红外波段采用阈值法提取Sentinel 2图像中的水分;然后,采用Otsu阈值算法,基于浮子碎片指数(Float Debris Index, FDI)对塑料网格进行识别和分类;研究中还采用了NDVI、NDWI等光谱指标来提高塑料网的分类精度。本研究还使用谷歌高空间分辨率卫星图像来评估塑料网格分类的准确性。结果表明,在02个测试区域中,该方法对塑料网格的检测精度达到90%以上。研究结果可为预测和评估海洋塑料垃圾污染对沿海环境影响的模型提供输入信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A method for detecting plastic waste floating using Sentinel 2 high spatial resolution image: a case study in the coastal area of Vietnam
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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来源期刊
CiteScore
0.90
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2
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