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Processing of Bathymetric Data: The Fusion of New Reduction Methods for Spatial Big Data
Floating autonomous vehicles are very often equipped with modern systems that collect information about the situation under the water surface, e.g., the depth or type of bottom and obstructions on the seafloor. One such system is the multibeam echosounder (MBES), which collects very large sets of ba...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662608/ https://www.ncbi.nlm.nih.gov/pubmed/33143323 http://dx.doi.org/10.3390/s20216207 |
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author | Wlodarczyk-Sielicka, Marta Blaszczak-Bak, Wioleta |
author_facet | Wlodarczyk-Sielicka, Marta Blaszczak-Bak, Wioleta |
author_sort | Wlodarczyk-Sielicka, Marta |
collection | PubMed |
description | Floating autonomous vehicles are very often equipped with modern systems that collect information about the situation under the water surface, e.g., the depth or type of bottom and obstructions on the seafloor. One such system is the multibeam echosounder (MBES), which collects very large sets of bathymetric data. The development and analysis of such large sets are laborious and expensive. Reduction of the spatial data obtained from bathymetric and other systems collecting spatial data is currently widely used. In commercial programs used in the development of data from hydrographic systems, methods of interpolation to a specific mesh size are very frequently used. The authors of this article previously proposed original the true bathymetric data reduction method (TBDRed) and Optimum Dataset (OptD) reduction methods, which maintain the actual position and depth for each of the measured points, without their interpolation. The effectiveness of the proposed methods has already been presented in previous articles. This article proposes the fusion of original reduction methods, which is a new and innovative approach to the problem of bathymetric data reduction. The article contains a description of the methods used and the methodology of developing bathymetric data. The proposed fusion of reduction methods allows the generation of numerical models that can be a safe, reliable source of information, and a basis for design. Numerical models can also be used in comparative navigation, during the creation of electronic navigation maps and other hydrographic products. |
format | Online Article Text |
id | pubmed-7662608 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76626082020-11-14 Processing of Bathymetric Data: The Fusion of New Reduction Methods for Spatial Big Data Wlodarczyk-Sielicka, Marta Blaszczak-Bak, Wioleta Sensors (Basel) Article Floating autonomous vehicles are very often equipped with modern systems that collect information about the situation under the water surface, e.g., the depth or type of bottom and obstructions on the seafloor. One such system is the multibeam echosounder (MBES), which collects very large sets of bathymetric data. The development and analysis of such large sets are laborious and expensive. Reduction of the spatial data obtained from bathymetric and other systems collecting spatial data is currently widely used. In commercial programs used in the development of data from hydrographic systems, methods of interpolation to a specific mesh size are very frequently used. The authors of this article previously proposed original the true bathymetric data reduction method (TBDRed) and Optimum Dataset (OptD) reduction methods, which maintain the actual position and depth for each of the measured points, without their interpolation. The effectiveness of the proposed methods has already been presented in previous articles. This article proposes the fusion of original reduction methods, which is a new and innovative approach to the problem of bathymetric data reduction. The article contains a description of the methods used and the methodology of developing bathymetric data. The proposed fusion of reduction methods allows the generation of numerical models that can be a safe, reliable source of information, and a basis for design. Numerical models can also be used in comparative navigation, during the creation of electronic navigation maps and other hydrographic products. MDPI 2020-10-30 /pmc/articles/PMC7662608/ /pubmed/33143323 http://dx.doi.org/10.3390/s20216207 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wlodarczyk-Sielicka, Marta Blaszczak-Bak, Wioleta Processing of Bathymetric Data: The Fusion of New Reduction Methods for Spatial Big Data |
title | Processing of Bathymetric Data: The Fusion of New Reduction Methods for Spatial Big Data |
title_full | Processing of Bathymetric Data: The Fusion of New Reduction Methods for Spatial Big Data |
title_fullStr | Processing of Bathymetric Data: The Fusion of New Reduction Methods for Spatial Big Data |
title_full_unstemmed | Processing of Bathymetric Data: The Fusion of New Reduction Methods for Spatial Big Data |
title_short | Processing of Bathymetric Data: The Fusion of New Reduction Methods for Spatial Big Data |
title_sort | processing of bathymetric data: the fusion of new reduction methods for spatial big data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662608/ https://www.ncbi.nlm.nih.gov/pubmed/33143323 http://dx.doi.org/10.3390/s20216207 |
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