Mahmud, Mohd. Razali and Mohd. Yusof, Othman (2006) General workflow for outliers detection and removal in multibeam echo sounding data. In: Hydrography Survey: Current Trends, Techniques and Applications. Penerbit UTM, Johor , 165 - 180. ISBN 978-983-52-0581-1
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Official URL: http://www.penerbit.utm.my/bookchapterdoc/FKSG/boo...
A multibeam echosounder (MBES) is gaining a wide popularity in sounding works due to technology developments and its results. The capabilities of having 100% coverage with high data resolution have turned the system to be an alternative to a single beam echosounder. With high density of sounding data, one could have full details of the seabed. Although it sounds to be more advantages to have huge density of data, it cannot promise the data reliability. In other words, these highly dense data also contain erroneous data, called outliers. The conventional method of detecting and deleting outlier data using line-by-line visual inspection work is very tedious and time consuming. This issue could be addressed by establishing a general workflow that is capable of detecting and deleting the outliers. Before this could happens, a set of criteria in order to detect potential outliers and statistical tests prior to any deleting of the point, must be ascertained. Although it is a priority to remove the outliers, at the same time it is also a need to retain the good data. To decide whether the suspected point is true outlier or merely a good point, is quite tricky and sometime requires the need to turn back to traditional visual inspections. This paper elaborates the criteria needed and the sequence of the general workflow, designed for cleaning the outlier, before programming could take place.
|Item Type:||Book Section|
|Divisions:||Geoinformation Science And Engineering (Formerly known)|
|Deposited By:||Liza Porijo|
|Deposited On:||23 May 2012 07:43|
|Last Modified:||05 Feb 2017 03:33|
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