{"title":"杜马-鲁帕特岛拟建电力电缆线路侧扫声呐的声学特性","authors":"Subarsyah Subarsyah, Sahudin Sahudin","doi":"10.32693/bomg.38.1.2023.812","DOIUrl":null,"url":null,"abstract":"Cable power installation along the route with bedforms-sediment structures sometimes potentially to have problems in the future or near future. In order to mitigate the cable from exposure because of currents, it is important to know a detailed understanding of the seabed and its mobility. Seabed characteristics, either textures or sediment structures, could be interpreted from acoustic characters, one of which is based on sidescan sonar images. An automatic interpretation to classify seabed characteristics can be done by using an image processing software. Image processing has been done on sidescan sonar images along power cable route between Dumai and Rupat Island. The image processing was using simple textures and Grey-Level Co-occurrence Matrix (GCLM) textures. Manual interpretation of sidescan sonar images classifies the acoustic characters into six; (1) fine sand waves with ripple marks, wave length 2.5-4 meters, (2) fine sands, (3) fine sand waves with ripple marks, wave length 5-9 meters, (4) fine sand with ripple-mega ripples, (5) coarse sands with ripple-trawl marks, and (6) very fine sands. The results of automatic classification show that image processing with simple textures is unable to identify the textures and structures of sediments properly, but by combining simple texture classification and GCLM types of sediment textures and sediment structures are better identified. This classification results are in agreement with the results of manual interpretation of sidescan sonar images.","PeriodicalId":31610,"journal":{"name":"Bulletin of the Marine Geology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ACOUSTIC CHARACTERISTICS OF SIDESCAN SONAR ALONG PROPOSED POWER CABLE ROUTE, DUMAI – RUPAT ISLAND\",\"authors\":\"Subarsyah Subarsyah, Sahudin Sahudin\",\"doi\":\"10.32693/bomg.38.1.2023.812\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cable power installation along the route with bedforms-sediment structures sometimes potentially to have problems in the future or near future. In order to mitigate the cable from exposure because of currents, it is important to know a detailed understanding of the seabed and its mobility. Seabed characteristics, either textures or sediment structures, could be interpreted from acoustic characters, one of which is based on sidescan sonar images. An automatic interpretation to classify seabed characteristics can be done by using an image processing software. Image processing has been done on sidescan sonar images along power cable route between Dumai and Rupat Island. The image processing was using simple textures and Grey-Level Co-occurrence Matrix (GCLM) textures. Manual interpretation of sidescan sonar images classifies the acoustic characters into six; (1) fine sand waves with ripple marks, wave length 2.5-4 meters, (2) fine sands, (3) fine sand waves with ripple marks, wave length 5-9 meters, (4) fine sand with ripple-mega ripples, (5) coarse sands with ripple-trawl marks, and (6) very fine sands. The results of automatic classification show that image processing with simple textures is unable to identify the textures and structures of sediments properly, but by combining simple texture classification and GCLM types of sediment textures and sediment structures are better identified. This classification results are in agreement with the results of manual interpretation of sidescan sonar images.\",\"PeriodicalId\":31610,\"journal\":{\"name\":\"Bulletin of the Marine Geology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bulletin of the Marine Geology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32693/bomg.38.1.2023.812\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bulletin of the Marine Geology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32693/bomg.38.1.2023.812","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ACOUSTIC CHARACTERISTICS OF SIDESCAN SONAR ALONG PROPOSED POWER CABLE ROUTE, DUMAI – RUPAT ISLAND
Cable power installation along the route with bedforms-sediment structures sometimes potentially to have problems in the future or near future. In order to mitigate the cable from exposure because of currents, it is important to know a detailed understanding of the seabed and its mobility. Seabed characteristics, either textures or sediment structures, could be interpreted from acoustic characters, one of which is based on sidescan sonar images. An automatic interpretation to classify seabed characteristics can be done by using an image processing software. Image processing has been done on sidescan sonar images along power cable route between Dumai and Rupat Island. The image processing was using simple textures and Grey-Level Co-occurrence Matrix (GCLM) textures. Manual interpretation of sidescan sonar images classifies the acoustic characters into six; (1) fine sand waves with ripple marks, wave length 2.5-4 meters, (2) fine sands, (3) fine sand waves with ripple marks, wave length 5-9 meters, (4) fine sand with ripple-mega ripples, (5) coarse sands with ripple-trawl marks, and (6) very fine sands. The results of automatic classification show that image processing with simple textures is unable to identify the textures and structures of sediments properly, but by combining simple texture classification and GCLM types of sediment textures and sediment structures are better identified. This classification results are in agreement with the results of manual interpretation of sidescan sonar images.