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Measuring (subglacial) bedform orientation, length, and longitudinal asymmetry – Method assessment

Geospatial analysis software provides a range of tools that can be used to measure landform morphometry. Often, a metric can be computed with different techniques that may give different results. This study is an assessment of 5 different methods for measuring longitudinal, or streamlined, subglacia...

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Autores principales: Jorge, Marco G., Brennand, Tracy A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5358869/
https://www.ncbi.nlm.nih.gov/pubmed/28319132
http://dx.doi.org/10.1371/journal.pone.0174312
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author Jorge, Marco G.
Brennand, Tracy A.
author_facet Jorge, Marco G.
Brennand, Tracy A.
author_sort Jorge, Marco G.
collection PubMed
description Geospatial analysis software provides a range of tools that can be used to measure landform morphometry. Often, a metric can be computed with different techniques that may give different results. This study is an assessment of 5 different methods for measuring longitudinal, or streamlined, subglacial bedform morphometry: orientation, length and longitudinal asymmetry, all of which require defining a longitudinal axis. The methods use the standard deviational ellipse (not previously applied in this context), the longest straight line fitting inside the bedform footprint (2 approaches), the minimum-size footprint-bounding rectangle, and Euler’s approximation. We assess how well these methods replicate morphometric data derived from a manually mapped (visually interpreted) longitudinal axis, which, though subjective, is the most typically used reference. A dataset of 100 subglacial bedforms covering the size and shape range of those in the Puget Lowland, Washington, USA is used. For bedforms with elongation > 5, deviations from the reference values are negligible for all methods but Euler’s approximation (length). For bedforms with elongation < 5, most methods had small mean absolute error (MAE) and median absolute deviation (MAD) for all morphometrics and thus can be confidently used to characterize the central tendencies of their distributions. However, some methods are better than others. The least precise methods are the ones based on the longest straight line and Euler’s approximation; using these for statistical dispersion analysis is discouraged. Because the standard deviational ellipse method is relatively shape invariant and closely replicates the reference values, it is the recommended method. Speculatively, this study may also apply to negative-relief, and fluvial and aeolian bedforms.
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spelling pubmed-53588692017-04-06 Measuring (subglacial) bedform orientation, length, and longitudinal asymmetry – Method assessment Jorge, Marco G. Brennand, Tracy A. PLoS One Research Article Geospatial analysis software provides a range of tools that can be used to measure landform morphometry. Often, a metric can be computed with different techniques that may give different results. This study is an assessment of 5 different methods for measuring longitudinal, or streamlined, subglacial bedform morphometry: orientation, length and longitudinal asymmetry, all of which require defining a longitudinal axis. The methods use the standard deviational ellipse (not previously applied in this context), the longest straight line fitting inside the bedform footprint (2 approaches), the minimum-size footprint-bounding rectangle, and Euler’s approximation. We assess how well these methods replicate morphometric data derived from a manually mapped (visually interpreted) longitudinal axis, which, though subjective, is the most typically used reference. A dataset of 100 subglacial bedforms covering the size and shape range of those in the Puget Lowland, Washington, USA is used. For bedforms with elongation > 5, deviations from the reference values are negligible for all methods but Euler’s approximation (length). For bedforms with elongation < 5, most methods had small mean absolute error (MAE) and median absolute deviation (MAD) for all morphometrics and thus can be confidently used to characterize the central tendencies of their distributions. However, some methods are better than others. The least precise methods are the ones based on the longest straight line and Euler’s approximation; using these for statistical dispersion analysis is discouraged. Because the standard deviational ellipse method is relatively shape invariant and closely replicates the reference values, it is the recommended method. Speculatively, this study may also apply to negative-relief, and fluvial and aeolian bedforms. Public Library of Science 2017-03-20 /pmc/articles/PMC5358869/ /pubmed/28319132 http://dx.doi.org/10.1371/journal.pone.0174312 Text en © 2017 Jorge, Brennand http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Jorge, Marco G.
Brennand, Tracy A.
Measuring (subglacial) bedform orientation, length, and longitudinal asymmetry – Method assessment
title Measuring (subglacial) bedform orientation, length, and longitudinal asymmetry – Method assessment
title_full Measuring (subglacial) bedform orientation, length, and longitudinal asymmetry – Method assessment
title_fullStr Measuring (subglacial) bedform orientation, length, and longitudinal asymmetry – Method assessment
title_full_unstemmed Measuring (subglacial) bedform orientation, length, and longitudinal asymmetry – Method assessment
title_short Measuring (subglacial) bedform orientation, length, and longitudinal asymmetry – Method assessment
title_sort measuring (subglacial) bedform orientation, length, and longitudinal asymmetry – method assessment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5358869/
https://www.ncbi.nlm.nih.gov/pubmed/28319132
http://dx.doi.org/10.1371/journal.pone.0174312
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