Generating higher resolution regional seafloor maps from crowd-sourced bathymetry

PLoS One. 2019 Jun 10;14(6):e0216792. doi: 10.1371/journal.pone.0216792. eCollection 2019.

Abstract

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 km2 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Crowdsourcing*
  • Oceanography / methods*
  • Signal-To-Noise Ratio

Grants and funding

The research presented here was conducted in partial fulfillment of E.N.'s doctoral thesis, which is supported by the National Science and Engineering Research Council of Canada (NSERC Post-Graduate Scholarship). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.