利用神经网络技术检测北极海冰雷达图像中的铅含量

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-06-27 DOI:10.3103/s1068373924040083

N. Yu. Zakhvatkina, I. A. Bychkova, V. G. Smirnov

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引用次数: 0

摘要

摘要本文介绍了一种利用 "哨兵-1 号 "卫星在超宽扫描模式下提供的双偏振合成孔径雷达（SAR）数据从海冰中区分线索的算法。该算法利用合成孔径雷达图像中获得的海面信号的极化特征：共极化和交叉极化之间的比率。提出了一种对合成孔径雷达图像进行分类的技术，利用极化比和极化差以及纹理特征和神经网络实现来识别漂移海冰中的不连续性（裂缝、引线）。利用在俄罗斯联邦北极海域获得的卫星数据对该方法进行了测试。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Using the Neural Network Technique for Lead Detection in Radar Images of Arctic Sea Ice

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Using the Neural Network Technique for Lead Detection in Radar Images of Arctic Sea Ice

Abstract

The paper describes an algorithm to differentiate leads from sea ice using the dual polarization synthetic aperture radar (SAR) data from the Sentinel-1 satellite in an extrawide swath mode. The algorithm uses the polarimetric features of the sea surface signal obtained in the SAR images: the ratio between co- and cross-polarization. A technique is proposed for classifying the SAR images to identify discontinuities (cracks, leads) in drifting sea ice using the ratio and difference of polarizations together with texture features and the neural network implementation. The method was tested using the satellite data obtained over the Arctic seas in the Russian Federation.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.