Testing the Effect of Bathymetric Data Reduction on the Shape of the Digital Bottom Model
Depth data and the digital bottom model created from it are very important in the inland and coastal water zones studies and research. The paper undertakes the subject of bathymetric data processing using reduction methods and examines the impact of data reduction according to the resulting represen...
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Published in | Sensors (Basel, Switzerland) Vol. 23; no. 12; p. 5445 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
MDPI AG
08.06.2023
MDPI |
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Online Access | Get full text |
ISSN | 1424-8220 1424-8220 |
DOI | 10.3390/s23125445 |
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Abstract | Depth data and the digital bottom model created from it are very important in the inland and coastal water zones studies and research. The paper undertakes the subject of bathymetric data processing using reduction methods and examines the impact of data reduction according to the resulting representations of the bottom surface in the form of numerical bottom models. Data reduction is an approach that is meant to reduce the size of the input dataset to make it easier and more efficient for analysis, transmission, storage and similar. For the purposes of this article, test datasets were created by discretizing a selected polynomial function. The real dataset, which was used to verify the analyzes, was acquired using an interferometric echosounder mounted on a HydroDron-1 autonomous survey vessel. The data were collected in the ribbon of Lake Klodno, Zawory. Data reduction was conducted in two commercial programs. Three equal reduction parameters were adopted for each algorithm. The research part of the paper presents the results of the conducted analyzes of the reduced bathymetric datasets based on the visual comparison of numerical bottom models, isobaths, and statistical parameters. The article contains tabular results with statistics, as well as the spatial visualization of the studied fragments of numerical bottom models and isobaths. This research is being used in the course of work on an innovative project that aims to develop a prototype of a multi-dimensional and multi-temporal coastal zone monitoring system using autonomous, unmanned floating platforms at a single survey pass. |
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AbstractList | Depth data and the digital bottom model created from it are very important in the inland and coastal water zones studies and research. The paper undertakes the subject of bathymetric data processing using reduction methods and examines the impact of data reduction according to the resulting representations of the bottom surface in the form of numerical bottom models. Data reduction is an approach that is meant to reduce the size of the input dataset to make it easier and more efficient for analysis, transmission, storage and similar. For the purposes of this article, test datasets were created by discretizing a selected polynomial function. The real dataset, which was used to verify the analyzes, was acquired using an interferometric echosounder mounted on a HydroDron-1 autonomous survey vessel. The data were collected in the ribbon of Lake Klodno, Zawory. Data reduction was conducted in two commercial programs. Three equal reduction parameters were adopted for each algorithm. The research part of the paper presents the results of the conducted analyzes of the reduced bathymetric datasets based on the visual comparison of numerical bottom models, isobaths, and statistical parameters. The article contains tabular results with statistics, as well as the spatial visualization of the studied fragments of numerical bottom models and isobaths. This research is being used in the course of work on an innovative project that aims to develop a prototype of a multi-dimensional and multi-temporal coastal zone monitoring system using autonomous, unmanned floating platforms at a single survey pass. Depth data and the digital bottom model created from it are very important in the inland and coastal water zones studies and research. The paper undertakes the subject of bathymetric data processing using reduction methods and examines the impact of data reduction according to the resulting representations of the bottom surface in the form of numerical bottom models. Data reduction is an approach that is meant to reduce the size of the input dataset to make it easier and more efficient for analysis, transmission, storage and similar. For the purposes of this article, test datasets were created by discretizing a selected polynomial function. The real dataset, which was used to verify the analyzes, was acquired using an interferometric echosounder mounted on a HydroDron-1 autonomous survey vessel. The data were collected in the ribbon of Lake Klodno, Zawory. Data reduction was conducted in two commercial programs. Three equal reduction parameters were adopted for each algorithm. The research part of the paper presents the results of the conducted analyzes of the reduced bathymetric datasets based on the visual comparison of numerical bottom models, isobaths, and statistical parameters. The article contains tabular results with statistics, as well as the spatial visualization of the studied fragments of numerical bottom models and isobaths. This research is being used in the course of work on an innovative project that aims to develop a prototype of a multi-dimensional and multi-temporal coastal zone monitoring system using autonomous, unmanned floating platforms at a single survey pass.Depth data and the digital bottom model created from it are very important in the inland and coastal water zones studies and research. The paper undertakes the subject of bathymetric data processing using reduction methods and examines the impact of data reduction according to the resulting representations of the bottom surface in the form of numerical bottom models. Data reduction is an approach that is meant to reduce the size of the input dataset to make it easier and more efficient for analysis, transmission, storage and similar. For the purposes of this article, test datasets were created by discretizing a selected polynomial function. The real dataset, which was used to verify the analyzes, was acquired using an interferometric echosounder mounted on a HydroDron-1 autonomous survey vessel. The data were collected in the ribbon of Lake Klodno, Zawory. Data reduction was conducted in two commercial programs. Three equal reduction parameters were adopted for each algorithm. The research part of the paper presents the results of the conducted analyzes of the reduced bathymetric datasets based on the visual comparison of numerical bottom models, isobaths, and statistical parameters. The article contains tabular results with statistics, as well as the spatial visualization of the studied fragments of numerical bottom models and isobaths. This research is being used in the course of work on an innovative project that aims to develop a prototype of a multi-dimensional and multi-temporal coastal zone monitoring system using autonomous, unmanned floating platforms at a single survey pass. |
Audience | Academic |
Author | Wlodarczyk-Sielicka, Marta Stateczny, Andrzej Mujta, Wiktor |
AuthorAffiliation | 2 Faculty of Navigation, Maritime University of Szczecin, Waly Chrobrego 1-2, 70-500 Szczecin, Poland 3 Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Gabriela Narutowicza 11-12, 80-233 Gdansk, Poland 1 Marine Technology Ltd., 81-521 Gdynia, Poland |
AuthorAffiliation_xml | – name: 3 Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Gabriela Narutowicza 11-12, 80-233 Gdansk, Poland – name: 1 Marine Technology Ltd., 81-521 Gdynia, Poland – name: 2 Faculty of Navigation, Maritime University of Szczecin, Waly Chrobrego 1-2, 70-500 Szczecin, Poland |
Author_xml | – sequence: 1 givenname: Wiktor surname: Mujta fullname: Mujta, Wiktor – sequence: 2 givenname: Marta orcidid: 0000-0002-7489-8437 surname: Wlodarczyk-Sielicka fullname: Wlodarczyk-Sielicka, Marta – sequence: 3 givenname: Andrzej orcidid: 0000-0002-4671-6827 surname: Stateczny fullname: Stateczny, Andrzej |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37420612$$D View this record in MEDLINE/PubMed |
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Cites_doi | 10.1029/94JB00988 10.1029/2021EA002069 10.3390/s20216207 10.1201/9781420008432 10.1016/j.epsl.2008.03.056 10.1029/2019EA000658 10.1002/gdj3.122 10.1121/1.422177 10.1016/j.patrec.2005.09.004 10.1109/JOE.2022.3220330 10.3390/s22051844 10.1088/1361-6501/aa7444 10.3390/jmse10010101 10.1016/B978-0-444-53446-0.00017-3 10.1016/j.ins.2003.06.013 10.1093/gji/ggab052 10.1109/ACCESS.2019.2938264 10.1002/jgrc.20199 10.3390/rs11131610 10.1016/j.crte.2006.05.014 10.1007/s11001-005-2095-4 10.3390/jmse10101349 10.1016/j.geomorph.2014.03.008 10.1016/j.rse.2020.112035 10.1029/93JB00716 10.3389/fmars.2019.00283 10.1080/09613218.2020.1729687 10.23919/OCEANS40490.2019.8962802 10.1109/BGC.Geomatics.2016.22 |
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Keywords | hydrography data reduction big data applications data processing bathymetry bathymetric data bottom model data visualization |
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SubjectTerms | Acoustics Algorithms Analysis bathymetry big data applications data processing data reduction Data visualization Datasets Geospatial data hydrography Propagation Surveys and Questionnaires Topography |
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Title | Testing the Effect of Bathymetric Data Reduction on the Shape of the Digital Bottom Model |
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