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A Method of DTM Construction Based on Quadrangular Irregular Networks and Related Error Analysis

A new method of DTM construction based on quadrangular irregular networks (QINs) that considers all the original data points and has a topological matrix is presented. A numerical test and a real-world example are used to comparatively analyse the accuracy of QINs against classical interpolation met...

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Detalles Bibliográficos
Autores principales: Kang, Mengjun, Wang, Mingjun, Du, Qingyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4440715/
https://www.ncbi.nlm.nih.gov/pubmed/25996691
http://dx.doi.org/10.1371/journal.pone.0127592
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author Kang, Mengjun
Wang, Mingjun
Du, Qingyun
author_facet Kang, Mengjun
Wang, Mingjun
Du, Qingyun
author_sort Kang, Mengjun
collection PubMed
description A new method of DTM construction based on quadrangular irregular networks (QINs) that considers all the original data points and has a topological matrix is presented. A numerical test and a real-world example are used to comparatively analyse the accuracy of QINs against classical interpolation methods and other DTM representation methods, including SPLINE, KRIGING and triangulated irregular networks (TINs). The numerical test finds that the QIN method is the second-most accurate of the four methods. In the real-world example, DTMs are constructed using QINs and the three classical interpolation methods. The results indicate that the QIN method is the most accurate method tested. The difference in accuracy rank seems to be caused by the locations of the data points sampled. Although the QIN method has drawbacks, it is an alternative method for DTM construction.
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spelling pubmed-44407152015-05-29 A Method of DTM Construction Based on Quadrangular Irregular Networks and Related Error Analysis Kang, Mengjun Wang, Mingjun Du, Qingyun PLoS One Research Article A new method of DTM construction based on quadrangular irregular networks (QINs) that considers all the original data points and has a topological matrix is presented. A numerical test and a real-world example are used to comparatively analyse the accuracy of QINs against classical interpolation methods and other DTM representation methods, including SPLINE, KRIGING and triangulated irregular networks (TINs). The numerical test finds that the QIN method is the second-most accurate of the four methods. In the real-world example, DTMs are constructed using QINs and the three classical interpolation methods. The results indicate that the QIN method is the most accurate method tested. The difference in accuracy rank seems to be caused by the locations of the data points sampled. Although the QIN method has drawbacks, it is an alternative method for DTM construction. Public Library of Science 2015-05-21 /pmc/articles/PMC4440715/ /pubmed/25996691 http://dx.doi.org/10.1371/journal.pone.0127592 Text en © 2015 Kang et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Kang, Mengjun
Wang, Mingjun
Du, Qingyun
A Method of DTM Construction Based on Quadrangular Irregular Networks and Related Error Analysis
title A Method of DTM Construction Based on Quadrangular Irregular Networks and Related Error Analysis
title_full A Method of DTM Construction Based on Quadrangular Irregular Networks and Related Error Analysis
title_fullStr A Method of DTM Construction Based on Quadrangular Irregular Networks and Related Error Analysis
title_full_unstemmed A Method of DTM Construction Based on Quadrangular Irregular Networks and Related Error Analysis
title_short A Method of DTM Construction Based on Quadrangular Irregular Networks and Related Error Analysis
title_sort method of dtm construction based on quadrangular irregular networks and related error analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4440715/
https://www.ncbi.nlm.nih.gov/pubmed/25996691
http://dx.doi.org/10.1371/journal.pone.0127592
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