Automated Filtering and Attribution of Archive Bathymetry Based on A Priori Knowledge

<p>Hydrographic offices hold large volumes of historical bathymetric data. Many of these valuable datasets were collected using older generation survey systems and contain little or no metadata. Current efforts to utilize these data require human intervention to remove outliers and assess quality. This thesis develops automated algorithms based on a priori knowledge of existing bathymetric topography to remove errant soundings and concurrently provide an estimate of uncertainty.</p>

Name thesis:degree_name

Master of Science (MS)

Level thesis:degree_level

Masters Thesis

Discipline thesis:degree_discipline

Computing

Year dc:date.available

2013

Author dc:creator

• Ladner, Rodney Wade

Contributors dc:contributor

• Louise Perkins
• Paul Elmore

• Computer Sciences
• Physical Sciences and Mathematics

Repository record dc:identifier

https://aquila.usm.edu/masters_theses/381

OAI identifier oai:identifier

oai:aquila.usm.edu:masters_theses-1451