کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
507550 | 865129 | 2012 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Multibeam echosounder data cleaning through a hierarchic adaptive and robust local surfacing Multibeam echosounder data cleaning through a hierarchic adaptive and robust local surfacing](/preview/png/507550.png)
Multibeam echo sounders (MBES) datasets generally contain sporadic outlier points. The huge volumes of MBES datasets in a hydrographic framework require the use of semi-automatic techniques. In very shallow waters depth, data cleaning becomes a challenging task when potential dangers to navigation have to be carefully checked. The aim of our paper is to attempt this goal by combining two well-known techniques. The seafloor is constructed as an assemblage of surface elements with the help of a robust statistical approach. The local parameters model is a priori chosen, its scale is driven through a quadtree descending approach using subdivision rules based on both statistical and spatio-temporal inferences. Our multi resolution approach provides, with the algorithm outputs, a classification map that notes areas of concern.
► Our algorithm is dedicated to MBES data cleaning.
► It combines a robust estimator with a quadtree descending technique.
► The adaptive algorithm scheme uses MBES data in both geographical and time reference frames.
► Our algorithm provides a valid sounding dataset supplemented by a confidence level map.
► The performance of the algorithm is validated for artificial and real datasets.
Journal: Computers & Geosciences - Volume 46, September 2012, Pages 330–339