Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESs

The paper presents an optimized method of digital terrain model (DTM) estimation based on modified kriging interpolation. Many methods are used for digital terrain model creation; the most popular methods are: inverse distance weighing, nearest neighbour, moving average, and kriging. The latter is o...

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Main Author: Maleika Wojciech
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Geosciences
Subjects:
Online Access:https://www.mdpi.com/2076-3263/8/12/433
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spelling doaj-b53a0b2d92034be58421ac8211a30d2c2020-11-25T00:05:31ZengMDPI AGGeosciences2076-32632018-11-0181243310.3390/geosciences8120433geosciences8120433Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESsMaleika Wojciech0Faculty of Computer Science, West Pomeranian University of Technology, Szczecin Zolnierska 49, 71-210 Szczecin, PolandThe paper presents an optimized method of digital terrain model (DTM) estimation based on modified kriging interpolation. Many methods are used for digital terrain model creation; the most popular methods are: inverse distance weighing, nearest neighbour, moving average, and kriging. The latter is often considered to be one of the best methods for interpolation of non-uniform spatial data, but the good results with respect to model’s accuracy come at the price of very long computational time. In this study, the optimization of the kriging method was performed for the purpose of seabed DTM creation based on millions of measurement points obtained from a multibeam echosounder device (MBES). The purpose of the optimization was to significantly decrease computation time, while maintaining the highest possible accuracy of created model. Several variants of kriging method were analysed (depending on search radius, minimum of required points, fixed number of points, and used smoothing method). The analysis resulted in a proposed optimization of the kriging method, utilizing a new technique of neighbouring points selection throughout the interpolation process (named “growing radius„). Experimental results proved the new kriging method to have significant advantages when applied to DTM estimation.https://www.mdpi.com/2076-3263/8/12/433kriging interpolationDTM creationMBES
collection DOAJ
language English
format Article
sources DOAJ
author Maleika Wojciech
spellingShingle Maleika Wojciech
Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESs
Geosciences
kriging interpolation
DTM creation
MBES
author_facet Maleika Wojciech
author_sort Maleika Wojciech
title Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESs
title_short Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESs
title_full Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESs
title_fullStr Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESs
title_full_unstemmed Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESs
title_sort kriging method optimization for the process of dtm creation based on huge data sets obtained from mbess
publisher MDPI AG
series Geosciences
issn 2076-3263
publishDate 2018-11-01
description The paper presents an optimized method of digital terrain model (DTM) estimation based on modified kriging interpolation. Many methods are used for digital terrain model creation; the most popular methods are: inverse distance weighing, nearest neighbour, moving average, and kriging. The latter is often considered to be one of the best methods for interpolation of non-uniform spatial data, but the good results with respect to model’s accuracy come at the price of very long computational time. In this study, the optimization of the kriging method was performed for the purpose of seabed DTM creation based on millions of measurement points obtained from a multibeam echosounder device (MBES). The purpose of the optimization was to significantly decrease computation time, while maintaining the highest possible accuracy of created model. Several variants of kriging method were analysed (depending on search radius, minimum of required points, fixed number of points, and used smoothing method). The analysis resulted in a proposed optimization of the kriging method, utilizing a new technique of neighbouring points selection throughout the interpolation process (named “growing radius„). Experimental results proved the new kriging method to have significant advantages when applied to DTM estimation.
topic kriging interpolation
DTM creation
MBES
url https://www.mdpi.com/2076-3263/8/12/433
work_keys_str_mv AT maleikawojciech krigingmethodoptimizationfortheprocessofdtmcreationbasedonhugedatasetsobtainedfrommbess
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