海洋塑料垃圾卫星遥感探测方法

doi:10.13474/j.cnki.11-2246.2023.0163

测绘通报 ›› 2023, Vol. 0 ›› Issue (6): 20-26.doi: 10.13474/j.cnki.11-2246.2023.0163

海洋塑料垃圾卫星遥感探测方法

李鹏^1,2, 周虹利^1,2, 林是聪^1,2, 王厚杰^1,2, 李振洪³

1. 中国海洋大学海洋地球科学学院河口海岸带研究所海底科学与探测技术教育部重点实验室, 山东青岛 266100;
2. 青岛海洋科学与技术国家实验室海洋地质过程与环境功能实验室, 山东青岛 266061;
3. 长安大学地质工程与测绘学院, 陕西西安 710054

收稿日期:2022-08-14 发布日期:2023-07-05
通讯作者: 周虹利。E-mail:zhouhongli@stu.ouc.edu.cn
作者简介:李鹏(1984-),男,博士,副教授,主要从事河口海岸带环境遥感研究。E-mail:pengli@ouc.edu.cn
基金资助:
国家自然科学基金(42041005-4)

A satellite remote sensing method for detecting marine plastic debirs

LI Peng^1,2, ZHOU Hongli^1,2, LIN Shicong^1,2, WANG Houjie^1,2, LI Zhenhong³

1. Key Lab of Submarine Geosciences and Prospecting Technology, Institute of Estuarine and Coastal Zone, College of Marine Geosciences, Ocean University of China, Qingdao 266100, China;
2. Laboratory of Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266061, China;
3. College of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China

Received:2022-08-14 Published:2023-07-05

摘要/Abstract

摘要： 海洋塑料垃圾广泛分布于近岸海域、大洋环流带等表层水体,严重危害海洋生物与人类社会可持续发展。受海洋塑料目标样本少、尺度小及卫星遥感传感器空间分辨率的限制,精确探测海洋塑料垃圾的时空分布特征具有重要的现实意义。本文利用Sentinel-2卫星遥感影像,基于已知海上塑料和其他漂浮物光谱特征,提出了一种反射率特征分类方法,用于探测与识别全球多个海域的海上漂浮塑料。该方法通过结合不同波段的反射率阈值与峰值特点,总体精度达到98%,F值为0.85,优于传统机器学习分类方法,有助于海洋塑料垃圾的变化探测与影响机制研究。

关键词: 海洋塑料垃圾, 光谱反射率, 海岸带, Sentinel-2, 机器学习

Abstract: Marine floating plastic debris is widely distributed in surface waters such as coastal waters and ocean gyres, which seriously endangers marine life and the sustainable development of human society. Limited by the small-scale, small number of marine plastic target samples and the spatial resolution of satellite remote sensing sensors, accurately detect the spatial and temporal distribution characteristics of marine plastic debris has an important practical significance. Based on the known spectral characteristics of plastic and other floating objects in the sea, this study proposes a reflectance feature classification method based on Sentinel-2 satellite imagery. By combining the reflectance threshold and peak characteristics of different bands, it can effectively detect and identify floating plastic in multiple regions of the world, with an overall accuracy of 98% and an F-score of 0.85, which is better than the traditional machine learning classification method, and is beneficial for the change detection and impact mechanism research of marine plastic debris.

Key words: marine plastic debris, spectral reflectance, coastal zone, Sentinel-2, machine learning

中图分类号:

P237

李鹏, 周虹利, 林是聪, 王厚杰, 李振洪. 海洋塑料垃圾卫星遥感探测方法[J]. 测绘通报, 2023, 0(6): 20-26.

LI Peng, ZHOU Hongli, LIN Shicong, WANG Houjie, LI Zhenhong. A satellite remote sensing method for detecting marine plastic debirs[J]. Bulletin of Surveying and Mapping, 2023, 0(6): 20-26.

参考文献

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海洋塑料垃圾卫星遥感探测方法

A satellite remote sensing method for detecting marine plastic debirs

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