{"title":"Application of Convolutional Neural Networks for Detecting Sea Ice Leads in the Laptev Sea with Landsat-8 Satellite Imagery","authors":"K. G. Kortikova, I. A. Bychkova","doi":"10.3103/s1068373924040046","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>A method for detecting leads in the ice of the Arctic seas from satellite images of the visible range is presented. It is shown that sea ice leads are formed under the influence of dynamic processes in the ice cover, such as convergence, drift, and deformation of sea ice, as well as during the interaction of drifting ice with icebergs that have gone aground. The method for identifying sea ice leads is based on the use of artificial intelligence. To analyze the Landsat-8 satellite imagery, a convolutional neural network (U-Net architecture) was used. The method was tested using the satellite images of the visible spectral range that were obtained for the Laptev Sea. The results showed that the lead detection accuracy was above 80%. The method of the minimum rotated rectangle surrounding the polygon was used to determine the geometric parameters of the leads (length, width, inflection points).</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Meteorology and Hydrology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.3103/s1068373924040046","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
A method for detecting leads in the ice of the Arctic seas from satellite images of the visible range is presented. It is shown that sea ice leads are formed under the influence of dynamic processes in the ice cover, such as convergence, drift, and deformation of sea ice, as well as during the interaction of drifting ice with icebergs that have gone aground. The method for identifying sea ice leads is based on the use of artificial intelligence. To analyze the Landsat-8 satellite imagery, a convolutional neural network (U-Net architecture) was used. The method was tested using the satellite images of the visible spectral range that were obtained for the Laptev Sea. The results showed that the lead detection accuracy was above 80%. The method of the minimum rotated rectangle surrounding the polygon was used to determine the geometric parameters of the leads (length, width, inflection points).
期刊介绍：
Russian Meteorology and Hydrology is a peer reviewed journal that covers topical issues of hydrometeorological science and practice: methods of forecasting weather and hydrological phenomena, climate monitoring issues, environmental pollution, space hydrometeorology, agrometeorology.
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