Processing RoxAnn sonar data to improve its categorization of lake bed surficial substrates†

被引:13
作者
Cholwek, G
Bonde, J
Li, X
Richards, C
Yin, K [1 ]
机构
[1] Univ Minnesota, Dept Wood & Paper Sci, St Paul, MN 55108 USA
[2] Univ Minnesota, Minnesota Sea Grant, Duluth, MN 55812 USA
[3] US Geol Survey, Great Lakes Sci Ctr, Lake Super Biol Stn, Ashland, WI 54806 USA
[4] Univ Minnesota, Nat Resources Res Inst, Duluth, MN 55812 USA
关键词
acoustic signals; bathymetry; bottom classification; fish habitat; Lake Superior; lake trout; multivariate statistics;
D O I
10.1023/A:1026525326823
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
To categorize spawning and nursery habitat for lake trout in Minnesota's near shore waters of Lake Superior, data was collected with a single beam echo sounder coupled with a RoxAnn bottom classification sensor. Test areas representative of the different bottom surficial substrates were sampled. The collected data consisted of acoustic signals which showed both depth and substrate type. The location of the signals was tagged in real-time with a DGPS. All data was imported into a GIS database. To better interpret the output signal from the RoxAnn, several pattern classifiers were developed by multivariate statistical method. From the data a detailed and accurate map of lake bed bathymetry and surficial substrate types was produced. This map will be of great value to fishery and other natural resource managers.
引用
收藏
页码:409 / 421
页数:13
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