ROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATAROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATA
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Boletim de Ciências Geodésicas |
Texto Completo: | https://revistas.ufpr.br/bcg/article/view/71707 |
Resumo: | Currently, during the operation in shallow waters, scanning systems, such as multibeam systems, are capable of collecting thousands of points in a short time, promoting a greater coverage of the submerged bottom, with consequent increase in the detection capacity of objects. Although there has been an improvement in the accuracy of the depths collected, traditional processing, that is, manual, is still required. However, mainly due to the increased mass of data collected, manual processing has become extremely time-consuming and subjective, especially in the detection and elimination of spikes. Several algorithms are used to perform this task, but most of them are based on statistical assumptions hardly met and/or verified, such as spatial independence and normality. In this sense, the goal of this study is to present the SODA (Spatial Outlier Detection Algorithm) methodology, a new method for detection of spikes designed to treat bathymetric data collected through swath bathymetry systems. From computational simulation, promising results were obtained. SODA, in some cases, was capable to identify even 90% of spikes inserted on simulation, showing that the methodology is efficient and substantial to the bathymetric data treatment. |
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Boletim de Ciências Geodésicas |
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ROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATAROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATAGeociências, Ciências da TerraSpikes; Outliers; Multibeam Echo Sounder; Multibeam Data Processing.Currently, during the operation in shallow waters, scanning systems, such as multibeam systems, are capable of collecting thousands of points in a short time, promoting a greater coverage of the submerged bottom, with consequent increase in the detection capacity of objects. Although there has been an improvement in the accuracy of the depths collected, traditional processing, that is, manual, is still required. However, mainly due to the increased mass of data collected, manual processing has become extremely time-consuming and subjective, especially in the detection and elimination of spikes. Several algorithms are used to perform this task, but most of them are based on statistical assumptions hardly met and/or verified, such as spatial independence and normality. In this sense, the goal of this study is to present the SODA (Spatial Outlier Detection Algorithm) methodology, a new method for detection of spikes designed to treat bathymetric data collected through swath bathymetry systems. From computational simulation, promising results were obtained. SODA, in some cases, was capable to identify even 90% of spikes inserted on simulation, showing that the methodology is efficient and substantial to the bathymetric data treatment.Boletim de Ciências GeodésicasBulletin of Geodetic SciencesFerreira, Italo OliveiraSantos, Afonso de Paula dosOliveira, Júlio César deMedeiros, Nilcilene das GraçasEmiliano, Paulo César2020-02-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ufpr.br/bcg/article/view/71707Boletim de Ciências Geodésicas; Vol 25, No 3 (2019)Bulletin of Geodetic Sciences; Vol 25, No 3 (2019)1982-21701413-4853reponame:Boletim de Ciências Geodésicasinstname:Universidade Federal do Paraná (UFPR)instacron:UFPRenghttps://revistas.ufpr.br/bcg/article/view/71707/40350Copyright (c) 2020 Italo Oliveira Ferreira, Afonso de Paula dos Santos, Júlio César de Oliveira, Nilcilene das Graças Medeiros, Paulo César Emilianohttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccess2020-02-13T16:19:47Zoai:revistas.ufpr.br:article/71707Revistahttps://revistas.ufpr.br/bcgPUBhttps://revistas.ufpr.br/bcg/oaiqdalmolin@ufpr.br|| danielsantos@ufpr.br||qdalmolin@ufpr.br|| danielsantos@ufpr.br1982-21701413-4853opendoar:2020-02-13T16:19:47Boletim de Ciências Geodésicas - Universidade Federal do Paraná (UFPR)false |
dc.title.none.fl_str_mv |
ROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATAROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATA |
title |
ROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATAROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATA |
spellingShingle |
ROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATAROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATA Ferreira, Italo Oliveira Geociências, Ciências da Terra Spikes; Outliers; Multibeam Echo Sounder; Multibeam Data Processing. |
title_short |
ROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATAROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATA |
title_full |
ROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATAROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATA |
title_fullStr |
ROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATAROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATA |
title_full_unstemmed |
ROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATAROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATA |
title_sort |
ROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATAROBUST METHODOLOGY FOR DETECTION OF SPIKES IN MULTIBEAM ECHO SOUNDER DATA |
author |
Ferreira, Italo Oliveira |
author_facet |
Ferreira, Italo Oliveira Santos, Afonso de Paula dos Oliveira, Júlio César de Medeiros, Nilcilene das Graças Emiliano, Paulo César |
author_role |
author |
author2 |
Santos, Afonso de Paula dos Oliveira, Júlio César de Medeiros, Nilcilene das Graças Emiliano, Paulo César |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
|
dc.contributor.author.fl_str_mv |
Ferreira, Italo Oliveira Santos, Afonso de Paula dos Oliveira, Júlio César de Medeiros, Nilcilene das Graças Emiliano, Paulo César |
dc.subject.none.fl_str_mv |
|
dc.subject.por.fl_str_mv |
Geociências, Ciências da Terra Spikes; Outliers; Multibeam Echo Sounder; Multibeam Data Processing. |
topic |
Geociências, Ciências da Terra Spikes; Outliers; Multibeam Echo Sounder; Multibeam Data Processing. |
description |
Currently, during the operation in shallow waters, scanning systems, such as multibeam systems, are capable of collecting thousands of points in a short time, promoting a greater coverage of the submerged bottom, with consequent increase in the detection capacity of objects. Although there has been an improvement in the accuracy of the depths collected, traditional processing, that is, manual, is still required. However, mainly due to the increased mass of data collected, manual processing has become extremely time-consuming and subjective, especially in the detection and elimination of spikes. Several algorithms are used to perform this task, but most of them are based on statistical assumptions hardly met and/or verified, such as spatial independence and normality. In this sense, the goal of this study is to present the SODA (Spatial Outlier Detection Algorithm) methodology, a new method for detection of spikes designed to treat bathymetric data collected through swath bathymetry systems. From computational simulation, promising results were obtained. SODA, in some cases, was capable to identify even 90% of spikes inserted on simulation, showing that the methodology is efficient and substantial to the bathymetric data treatment. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-02-13 |
dc.type.none.fl_str_mv |
|
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revistas.ufpr.br/bcg/article/view/71707 |
url |
https://revistas.ufpr.br/bcg/article/view/71707 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://revistas.ufpr.br/bcg/article/view/71707/40350 |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Boletim de Ciências Geodésicas Bulletin of Geodetic Sciences |
publisher.none.fl_str_mv |
Boletim de Ciências Geodésicas Bulletin of Geodetic Sciences |
dc.source.none.fl_str_mv |
Boletim de Ciências Geodésicas; Vol 25, No 3 (2019) Bulletin of Geodetic Sciences; Vol 25, No 3 (2019) 1982-2170 1413-4853 reponame:Boletim de Ciências Geodésicas instname:Universidade Federal do Paraná (UFPR) instacron:UFPR |
instname_str |
Universidade Federal do Paraná (UFPR) |
instacron_str |
UFPR |
institution |
UFPR |
reponame_str |
Boletim de Ciências Geodésicas |
collection |
Boletim de Ciências Geodésicas |
repository.name.fl_str_mv |
Boletim de Ciências Geodésicas - Universidade Federal do Paraná (UFPR) |
repository.mail.fl_str_mv |
qdalmolin@ufpr.br|| danielsantos@ufpr.br||qdalmolin@ufpr.br|| danielsantos@ufpr.br |
_version_ |
1799771719439745024 |