The application of acoustic seafloor habitat mapping using side-scan sonar image: The seafloor habitat and topography between Taiwan and Penghu Island

碩士 === 國立臺灣大學 === 海洋研究所 === 99 === In order to objectively analyze side-scan sonar image, we use SwathView which produced by QTC in Canada to process acoustic classification. We also use SwathView to analyze the data of area between Taiwan and Penghu Island. The main feature of SwathView is segmenta...

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Main Authors: Yi-Wei Chen, 陳益緯
Other Authors: Gwo-Shyh Song
Format: Others
Language:zh-TW
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/38907824544983142726
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spelling ndltd-TW-099NTU052790262015-10-16T04:03:08Z http://ndltd.ncl.edu.tw/handle/38907824544983142726 The application of acoustic seafloor habitat mapping using side-scan sonar image: The seafloor habitat and topography between Taiwan and Penghu Island 側掃聲納影像於海床底質測繪上的應用:台灣與澎湖間的海床底質與地貌 Yi-Wei Chen 陳益緯 碩士 國立臺灣大學 海洋研究所 99 In order to objectively analyze side-scan sonar image, we use SwathView which produced by QTC in Canada to process acoustic classification. We also use SwathView to analyze the data of area between Taiwan and Penghu Island. The main feature of SwathView is segmentation method; it combines many statistic algorithms and is useful to process large dataset. Every data has its own acoustic property; we classify the data which has the same acoustic property as one class and the others are so on. Firstly, we load each file and compensate it. Secondly, we segment sonar image by small rectangle, each small rectangle area has many backscatter intensity information. Thirdly, we calculate each rectangle area’s intensity value by statistic algorithms; each rectangle area has 29 statistic values. The last, we reduce 29 values to 3 principle values which called Q1, Q2, Q3 by PCA, according to these Q values we can define each rectangle area’s acoustic property and use K-means cluster method to classify each data. After classification by software, the result seems not well because some class has fake information. The most common fake information is along-track feature. Therefore we must process quality control. I devise the process of quality control by two steps: filter data before analysis and process data after analysis. After quality control we can get a good acoustic classification image. Then we can define each class by real habitat samples. Gwo-Shyh Song 宋國士 2011 學位論文 ; thesis 108 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 國立臺灣大學 === 海洋研究所 === 99 === In order to objectively analyze side-scan sonar image, we use SwathView which produced by QTC in Canada to process acoustic classification. We also use SwathView to analyze the data of area between Taiwan and Penghu Island. The main feature of SwathView is segmentation method; it combines many statistic algorithms and is useful to process large dataset. Every data has its own acoustic property; we classify the data which has the same acoustic property as one class and the others are so on. Firstly, we load each file and compensate it. Secondly, we segment sonar image by small rectangle, each small rectangle area has many backscatter intensity information. Thirdly, we calculate each rectangle area’s intensity value by statistic algorithms; each rectangle area has 29 statistic values. The last, we reduce 29 values to 3 principle values which called Q1, Q2, Q3 by PCA, according to these Q values we can define each rectangle area’s acoustic property and use K-means cluster method to classify each data. After classification by software, the result seems not well because some class has fake information. The most common fake information is along-track feature. Therefore we must process quality control. I devise the process of quality control by two steps: filter data before analysis and process data after analysis. After quality control we can get a good acoustic classification image. Then we can define each class by real habitat samples.
author2 Gwo-Shyh Song
author_facet Gwo-Shyh Song
Yi-Wei Chen
陳益緯
author Yi-Wei Chen
陳益緯
spellingShingle Yi-Wei Chen
陳益緯
The application of acoustic seafloor habitat mapping using side-scan sonar image: The seafloor habitat and topography between Taiwan and Penghu Island
author_sort Yi-Wei Chen
title The application of acoustic seafloor habitat mapping using side-scan sonar image: The seafloor habitat and topography between Taiwan and Penghu Island
title_short The application of acoustic seafloor habitat mapping using side-scan sonar image: The seafloor habitat and topography between Taiwan and Penghu Island
title_full The application of acoustic seafloor habitat mapping using side-scan sonar image: The seafloor habitat and topography between Taiwan and Penghu Island
title_fullStr The application of acoustic seafloor habitat mapping using side-scan sonar image: The seafloor habitat and topography between Taiwan and Penghu Island
title_full_unstemmed The application of acoustic seafloor habitat mapping using side-scan sonar image: The seafloor habitat and topography between Taiwan and Penghu Island
title_sort application of acoustic seafloor habitat mapping using side-scan sonar image: the seafloor habitat and topography between taiwan and penghu island
publishDate 2011
url http://ndltd.ncl.edu.tw/handle/38907824544983142726
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