Autonomous underwater vehicles (AUVs) are an emerging technology increasingly being employed in geoscience and ecosystem research in the Great Lakes, capitalizing on their ability to sample large areas fitted with a variety of sensors. Previous to AUV use, chlorophyll measurements were either collected at discrete locations accessed by boats or derived from satellite remote sensing data. An advantage of AUVs is the ability to detect the presence of subsurface formations such as a deep chlorophyll layer or directly measure features such as the extent of the photic zone, which provides the opportunity to compare these in situ measured features to those represented by surface sampling regimes. This study validates a data processing method for AUV—sampled data showing a strong match with satellite-derived surface chlorophyll values when comparing the first 10 meters of the water column. The presence of a deep chlorophyll layer during the time of data collection was confirmed, and maximum chlorophyll values within this layer were demonstrated to be significantly higher (on average 5.4 times) than what is represented by the satellite data sources. Calculation of the photic zone depth using in situ measurements and algorithms applied to remotely sensed data produced mixed results, with one method producing a close match and another showing the satellite input overestimating photic zone depth. These results bolster the need for further study of the accuracy of assessing system-wide biological processes using remotely sensed data sources.
","abstract_html":"<p>Autonomous underwater vehicles (AUVs) are an emerging technology increasingly being employed in geoscience and ecosystem research in the Great Lakes, capitalizing on their ability to sample large areas fitted with a variety of sensors. Previous to AUV use, chlorophyll measurements were either collected at discrete locations accessed by boats or derived from satellite remote sensing data. An advantage of AUVs is the ability to detect the presence of subsurface formations such as a deep chlorophyll layer or directly measure features such as the extent of the photic zone, which provides the opportunity to compare these in situ measured features to those represented by surface sampling regimes. This study validates a data processing method for AUV—sampled data showing a strong match with satellite-derived surface chlorophyll values when comparing the first 10 meters of the water column. The presence of a deep chlorophyll layer during the time of data collection was confirmed, and maximum chlorophyll values within this layer were demonstrated to be significantly higher (on average 5.4 times) than what is represented by the satellite data sources. Calculation of the photic zone depth using in situ measurements and algorithms applied to remotely sensed data produced mixed results, with one method producing a close match and another showing the satellite input overestimating photic zone depth. These results bolster the need for further study of the accuracy of assessing system-wide biological processes using remotely sensed data sources.</p>","abstract_has_math":false,"creators":["Bennion, David"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Open Access Dissertation","degree_discipline":"College of Technology","degree_department":null,"school":null,"contributors":["Yichun Xie, PhD","Deb de Laski-Smith, PhD","William Welsh, PhD"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-01-01T08:00:00Z","date_published":"2023-01-01T08:00:00Z","updated_at":"2026-07-24T02:17:47Z","subjects":["lake michgan","auv","chlorophyll","photic zone","Ecology and Evolutionary Biology","Environmental Studies","Geographic Information Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.emich.edu/theses/1218","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Yichun Xie, PhD","Deb de Laski-Smith, PhD","William Welsh, PhD"]},{"key":"dc:creator","label":"Author","values":["Bennion, David"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2024-02-21T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["College of Technology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["lake michgan","auv","chlorophyll","photic zone","Ecology and Evolutionary Biology","Environmental Studies","Geographic Information Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.emich.edu/theses/1218"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Autonomous underwater vehicles (AUVs) are an emerging technology increasingly being employed in geoscience and ecosystem research in the Great Lakes, capitalizing on their ability to sample large areas fitted with a variety of sensors. Previous to AUV use, chlorophyll measurements were either collected at discrete locations accessed by boats or derived from satellite remote sensing data. An advantage of AUVs is the ability to detect the presence of subsurface formations such as a deep chlorophyll layer or directly measure features such as the extent of the photic zone, which provides the opportunity to compare these in situ measured features to those represented by surface sampling regimes. This study validates a data processing method for AUV—sampled data showing a strong match with satellite-derived surface chlorophyll values when comparing the first 10 meters of the water column. The presence of a deep chlorophyll layer during the time of data collection was confirmed, and maximum chlorophyll values within this layer were demonstrated to be significantly higher (on average 5.4 times) than what is represented by the satellite data sources. Calculation of the photic zone depth using in situ measurements and algorithms applied to remotely sensed data produced mixed results, with one method producing a close match and another showing the satellite input overestimating photic zone depth. These results bolster the need for further study of the accuracy of assessing system-wide biological processes using remotely sensed data sources.
"]},{"key":"dc:title","label":"Title","values":["Comparison of water column properties derived from an autonomous underwater vehicle and satellite based sources in Lake Michigan"]}]}],"canonical_facts":{"dc:contributor":["Yichun Xie, PhD","Deb de Laski-Smith, PhD","William Welsh, PhD"],"dc:creator":["Bennion, David"],"dc:date.available":["2024-02-21T08:00:00Z"],"dc:description.abstract":["Autonomous underwater vehicles (AUVs) are an emerging technology increasingly being employed in geoscience and ecosystem research in the Great Lakes, capitalizing on their ability to sample large areas fitted with a variety of sensors. Previous to AUV use, chlorophyll measurements were either collected at discrete locations accessed by boats or derived from satellite remote sensing data. An advantage of AUVs is the ability to detect the presence of subsurface formations such as a deep chlorophyll layer or directly measure features such as the extent of the photic zone, which provides the opportunity to compare these in situ measured features to those represented by surface sampling regimes. This study validates a data processing method for AUV—sampled data showing a strong match with satellite-derived surface chlorophyll values when comparing the first 10 meters of the water column. The presence of a deep chlorophyll layer during the time of data collection was confirmed, and maximum chlorophyll values within this layer were demonstrated to be significantly higher (on average 5.4 times) than what is represented by the satellite data sources. Calculation of the photic zone depth using in situ measurements and algorithms applied to remotely sensed data produced mixed results, with one method producing a close match and another showing the satellite input overestimating photic zone depth. These results bolster the need for further study of the accuracy of assessing system-wide biological processes using remotely sensed data sources.
"],"dc:identifier":["https://commons.emich.edu/theses/1218"],"dc:subject":["lake michgan","auv","chlorophyll","photic zone","Ecology and Evolutionary Biology","Environmental Studies","Geographic Information Sciences"],"dc:title":["Comparison of water column properties derived from an autonomous underwater vehicle and satellite based sources in Lake Michigan"],"thesis:degree_discipline":["College of Technology"],"thesis:degree_level":["Open Access Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T02:17:47Z"}