Comparison of different spatial interpolation methods for historical hydrographic data of the lowermost Mississippi River

The lowermost Mississippi River (LMR) is important to the environment and economy of continental United States. Although bathymetric data have been collected over many decades at numerous cross-sectional sounding points, there has been no consensus on appropriate interpolator for generating bathymet...

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Main Authors: Chia-Yu Wu, Joann Mossa, Liang Mao, Mohammad Almulla
Format: Article
Language:English
Published: Taylor & Francis Group 2019-04-01
Series:Annals of GIS
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Online Access:https://www.tandfonline.com/doi/10.1080/19475683.2019.1588781
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author Chia-Yu Wu
Joann Mossa
Liang Mao
Mohammad Almulla
author_facet Chia-Yu Wu
Joann Mossa
Liang Mao
Mohammad Almulla
author_sort Chia-Yu Wu
collection DOAJ
description The lowermost Mississippi River (LMR) is important to the environment and economy of continental United States. Although bathymetric data have been collected over many decades at numerous cross-sectional sounding points, there has been no consensus on appropriate interpolator for generating bathymetry. Such interpolation is critical to reliable assessments of channel morphology and channel change, which serve for dredging, engineering projects, and mapping of navigation hazards. This study aimed to identify an optimal spatial interpolation for mapping the river bathymetry from cross-sectional sounding measurements. We evaluated a variety of spatial interpolation methods including Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Radial Basis Function (RBF), and Local Polynomial Interpolation (LPI). In addition, we also considered the anisotropic form of IDW (Elliptical IDW as EIDW), that of OK (OKA), and Universal Kriging (UK). Two reaches in the LMR, located between approximately RM (River Miles) 170–140 and RM 60–35, were chosen as the study area. Those interpolators were compared in terms of root-mean-square error (RMSE), mean absolute error (MAE), bias, and coefficient of determination (r2). Our results demonstrate that both of RBF and OKA performed the best in mapping the bathymetry of study reaches. Furthermore, our results also indicate that the addition of anisotropy can significantly reduce RMSE by 5–20%, as compared to isotropic methods. The findings better inform other researchers on selecting a proper interpolation technique for mapping river bathymetry, particularly for other reaches of the Mississippi River.
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spelling doaj-art-fcce8834f0644bd48a490d76d41fb0922024-12-17T09:59:30ZengTaylor & Francis GroupAnnals of GIS1947-56831947-56912019-04-0125213315110.1080/19475683.2019.1588781Comparison of different spatial interpolation methods for historical hydrographic data of the lowermost Mississippi RiverChia-Yu Wu0Joann Mossa1Liang Mao2Mohammad Almulla3Department of Geography, University of Florida, Gainesville, FL, USADepartment of Geography, University of Florida, Gainesville, FL, USADepartment of Geography, University of Florida, Gainesville, FL, USADepartment of Geography, University of Florida, Gainesville, FL, USAThe lowermost Mississippi River (LMR) is important to the environment and economy of continental United States. Although bathymetric data have been collected over many decades at numerous cross-sectional sounding points, there has been no consensus on appropriate interpolator for generating bathymetry. Such interpolation is critical to reliable assessments of channel morphology and channel change, which serve for dredging, engineering projects, and mapping of navigation hazards. This study aimed to identify an optimal spatial interpolation for mapping the river bathymetry from cross-sectional sounding measurements. We evaluated a variety of spatial interpolation methods including Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Radial Basis Function (RBF), and Local Polynomial Interpolation (LPI). In addition, we also considered the anisotropic form of IDW (Elliptical IDW as EIDW), that of OK (OKA), and Universal Kriging (UK). Two reaches in the LMR, located between approximately RM (River Miles) 170–140 and RM 60–35, were chosen as the study area. Those interpolators were compared in terms of root-mean-square error (RMSE), mean absolute error (MAE), bias, and coefficient of determination (r2). Our results demonstrate that both of RBF and OKA performed the best in mapping the bathymetry of study reaches. Furthermore, our results also indicate that the addition of anisotropy can significantly reduce RMSE by 5–20%, as compared to isotropic methods. The findings better inform other researchers on selecting a proper interpolation technique for mapping river bathymetry, particularly for other reaches of the Mississippi River.https://www.tandfonline.com/doi/10.1080/19475683.2019.1588781Bathymetryspatial interpolation methodshydrographical cross-sectionsMississippi River
spellingShingle Chia-Yu Wu
Joann Mossa
Liang Mao
Mohammad Almulla
Comparison of different spatial interpolation methods for historical hydrographic data of the lowermost Mississippi River
Annals of GIS
Bathymetry
spatial interpolation methods
hydrographical cross-sections
Mississippi River
title Comparison of different spatial interpolation methods for historical hydrographic data of the lowermost Mississippi River
title_full Comparison of different spatial interpolation methods for historical hydrographic data of the lowermost Mississippi River
title_fullStr Comparison of different spatial interpolation methods for historical hydrographic data of the lowermost Mississippi River
title_full_unstemmed Comparison of different spatial interpolation methods for historical hydrographic data of the lowermost Mississippi River
title_short Comparison of different spatial interpolation methods for historical hydrographic data of the lowermost Mississippi River
title_sort comparison of different spatial interpolation methods for historical hydrographic data of the lowermost mississippi river
topic Bathymetry
spatial interpolation methods
hydrographical cross-sections
Mississippi River
url https://www.tandfonline.com/doi/10.1080/19475683.2019.1588781
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