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.
","abstract_html":"<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>","abstract_has_math":false,"creators":["Ladner, Rodney Wade"],"institution":null,"degree_name":"Master of Science (MS)","degree_level":"Masters Thesis","degree_discipline":"Computing","degree_department":null,"school":null,"contributors":["Louise Perkins","Paul Elmore"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-05-01T07:00:00Z","date_published":"2013-05-01T07:00:00Z","updated_at":"2026-07-24T05:44:50Z","subjects":["Computer Sciences","Physical Sciences and Mathematics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://aquila.usm.edu/masters_theses/381","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Louise Perkins","Paul Elmore"]},{"key":"dc:creator","label":"Author","values":["Ladner, Rodney Wade"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-10-23T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computing"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Computer Sciences","Physical Sciences and Mathematics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://aquila.usm.edu/masters_theses/381"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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.
"]},{"key":"dc:title","label":"Title","values":["Automated Filtering and Attribution of Archive Bathymetry Based on A Priori Knowledge"]}]}],"canonical_facts":{"dc:contributor":["Louise Perkins","Paul Elmore"],"dc:creator":["Ladner, Rodney Wade"],"dc:date.available":["2018-10-23T07:00:00Z"],"dc:description.abstract":["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.
"],"dc:identifier":["https://aquila.usm.edu/masters_theses/381"],"dc:subject":["Computer Sciences","Physical Sciences and Mathematics"],"dc:title":["Automated Filtering and Attribution of Archive Bathymetry Based on A Priori Knowledge"],"thesis:degree_discipline":["Computing"],"thesis:degree_level":["Masters Thesis"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T05:44:50Z"}