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Generating higher resolution regional seafloor maps from crowd-sourced bathymetry

Seafloor mapping can offer important insights for marine management, spatial planning, and research in marine geology, ecology, and oceanography. Here, we present a method for generating regional bathymetry and geomorphometry maps from crowd-sourced depth soundings (Olex AS) for a small fraction of...

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Detalles Bibliográficos
Autores principales: Novaczek, Emilie, Devillers, Rodolphe, Edinger, Evan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6557478/
https://www.ncbi.nlm.nih.gov/pubmed/31181079
http://dx.doi.org/10.1371/journal.pone.0216792
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author Novaczek, Emilie
Devillers, Rodolphe
Edinger, Evan
author_facet Novaczek, Emilie
Devillers, Rodolphe
Edinger, Evan
author_sort Novaczek, Emilie
collection PubMed
description Seafloor mapping can offer important insights for marine management, spatial planning, and research in marine geology, ecology, and oceanography. Here, we present a method for generating regional bathymetry and geomorphometry maps from crowd-sourced depth soundings (Olex AS) for a small fraction of the cost of multibeam data collection over the same area. Empirical Bayesian Kriging was used to generate a continuous bathymetric surface from incomplete and, in some areas, sparse Olex coverage on the Newfoundland and Labrador shelves of eastern Canada. The result is a 75m bathymetric grid that provides over 100x finer spatial resolution than previously available for the majority of the 672,900 km(2) study area. The interpolated bathymetry was tested for accuracy against independent depth data provided by Fisheries and Oceans Canada (Spearman correlation = 0.99, p<0.001). Quantitative terrain attributes were generated to better understand seascape characteristics at multiple spatial scales, including slope, rugosity, aspect, and bathymetric position index. Landform classification was carried out using the geomorphons algorithm and a novel method for the identification of previously unmapped tributary canyons at the continental shelf edge are also presented to illustrate some of many potential benefits of crowd-sourced regional seafloor mapping.
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spelling pubmed-65574782019-06-17 Generating higher resolution regional seafloor maps from crowd-sourced bathymetry Novaczek, Emilie Devillers, Rodolphe Edinger, Evan PLoS One Research Article Seafloor mapping can offer important insights for marine management, spatial planning, and research in marine geology, ecology, and oceanography. Here, we present a method for generating regional bathymetry and geomorphometry maps from crowd-sourced depth soundings (Olex AS) for a small fraction of the cost of multibeam data collection over the same area. Empirical Bayesian Kriging was used to generate a continuous bathymetric surface from incomplete and, in some areas, sparse Olex coverage on the Newfoundland and Labrador shelves of eastern Canada. The result is a 75m bathymetric grid that provides over 100x finer spatial resolution than previously available for the majority of the 672,900 km(2) study area. The interpolated bathymetry was tested for accuracy against independent depth data provided by Fisheries and Oceans Canada (Spearman correlation = 0.99, p<0.001). Quantitative terrain attributes were generated to better understand seascape characteristics at multiple spatial scales, including slope, rugosity, aspect, and bathymetric position index. Landform classification was carried out using the geomorphons algorithm and a novel method for the identification of previously unmapped tributary canyons at the continental shelf edge are also presented to illustrate some of many potential benefits of crowd-sourced regional seafloor mapping. Public Library of Science 2019-06-10 /pmc/articles/PMC6557478/ /pubmed/31181079 http://dx.doi.org/10.1371/journal.pone.0216792 Text en © 2019 Novaczek 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 (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
Novaczek, Emilie
Devillers, Rodolphe
Edinger, Evan
Generating higher resolution regional seafloor maps from crowd-sourced bathymetry
title Generating higher resolution regional seafloor maps from crowd-sourced bathymetry
title_full Generating higher resolution regional seafloor maps from crowd-sourced bathymetry
title_fullStr Generating higher resolution regional seafloor maps from crowd-sourced bathymetry
title_full_unstemmed Generating higher resolution regional seafloor maps from crowd-sourced bathymetry
title_short Generating higher resolution regional seafloor maps from crowd-sourced bathymetry
title_sort generating higher resolution regional seafloor maps from crowd-sourced bathymetry
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6557478/
https://www.ncbi.nlm.nih.gov/pubmed/31181079
http://dx.doi.org/10.1371/journal.pone.0216792
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