High-Resolution Sampling of a River Plume Front with Uncrewed Underwater and Aerial Vehicles.
Saved in:
| Title: | High-Resolution Sampling of a River Plume Front with Uncrewed Underwater and Aerial Vehicles. |
|---|---|
| Authors: | Piffer-Braga, Agata1 (AUTHOR) agata.p.braga@gmail.com, MacDonald, Daniel G.1 (AUTHOR), Delatolas, Nikiforos1 (AUTHOR), Goodman, Louis2 (AUTHOR), Huguenard, Kimberly3 (AUTHOR), Whitney, Michael M.4 (AUTHOR), Cole, Kelly3 (AUTHOR), Spicer, Preston3 (AUTHOR) |
| Source: | Journal of Atmospheric & Oceanic Technology. Nov2025, Vol. 42 Issue 11, p1469-1485. 17p. |
| Subjects: | Sampling (Process), Ocean dynamics, Buoys, Regions of freshwater influence, Information processing, Drone photography, Submersibles |
| Abstract: | Sampling fast-propagating oceanic features is inherently challenging and demands versatile instrumentation and innovative strategies. This paper introduces a novel sampling strategy designed to capture such phenomena, exemplified by a river plume front. Our method revolves around modifying the preprogrammed pathway of an uncrewed underwater vehicle (UUV) to dynamically track and three-dimensionally sample the evolution of the front. To enable the UUV to follow the feature, we adapt the use of a drifting gateway buoy to be positioned and trapped at the front's convergence zone, allowing underway navigation relative to the buoy. In our demonstration, we showcase the effectiveness of this strategy by successfully conducting over 30 crossings of a river plume front within a 6-h window. The UUV sensors allowed a comprehensive assessment of key front characteristics, including density, velocity, and turbulence. Supplemental drone footage contributed to the overall picture and facilitated the transformation of the dataset into a front-following reference frame. This article provides an in-depth description of the deployment strategy and required postcollection data processing, including frontal crossing detection, the assessment of the frontal orientation from drone footage, and defining the plume bottom boundaries using backscatter intensity contours. Significance Statement: Sampling fast-moving ocean features is challenging and requires flexible tools and creative approaches. In this paper, we present a new method for tracking and studying such features, using a river plume front as an example. Our approach involves using a buoy trapped in the plume front, guiding an uncrewed underwater vehicle (UUV) to follow the front in real time while gathering detailed data. In our test, the UUV crossed the river plume front more than 30 times in 6 h, collecting information on water density, speed, and turbulence. Drone footage added context and helped us analyze the data. This paper explains how we carried out the study and processed the data, including how we detected and mapped the front. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Atmospheric & Oceanic Technology is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 191141359 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: High-Resolution Sampling of a River Plume Front with Uncrewed Underwater and Aerial Vehicles. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Piffer-Braga%2C+Agata%22">Piffer-Braga, Agata</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> agata.p.braga@gmail.com</i><br /><searchLink fieldCode="AR" term="%22MacDonald%2C+Daniel+G%2E%22">MacDonald, Daniel G.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Delatolas%2C+Nikiforos%22">Delatolas, Nikiforos</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Goodman%2C+Louis%22">Goodman, Louis</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Huguenard%2C+Kimberly%22">Huguenard, Kimberly</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Whitney%2C+Michael+M%2E%22">Whitney, Michael M.</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cole%2C+Kelly%22">Cole, Kelly</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Spicer%2C+Preston%22">Spicer, Preston</searchLink><relatesTo>3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Atmospheric+%26+Oceanic+Technology%22">Journal of Atmospheric & Oceanic Technology</searchLink>. Nov2025, Vol. 42 Issue 11, p1469-1485. 17p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Sampling+%28Process%29%22">Sampling (Process)</searchLink><br /><searchLink fieldCode="DE" term="%22Ocean+dynamics%22">Ocean dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Buoys%22">Buoys</searchLink><br /><searchLink fieldCode="DE" term="%22Regions+of+freshwater+influence%22">Regions of freshwater influence</searchLink><br /><searchLink fieldCode="DE" term="%22Information+processing%22">Information processing</searchLink><br /><searchLink fieldCode="DE" term="%22Drone+photography%22">Drone photography</searchLink><br /><searchLink fieldCode="DE" term="%22Submersibles%22">Submersibles</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Sampling fast-propagating oceanic features is inherently challenging and demands versatile instrumentation and innovative strategies. This paper introduces a novel sampling strategy designed to capture such phenomena, exemplified by a river plume front. Our method revolves around modifying the preprogrammed pathway of an uncrewed underwater vehicle (UUV) to dynamically track and three-dimensionally sample the evolution of the front. To enable the UUV to follow the feature, we adapt the use of a drifting gateway buoy to be positioned and trapped at the front's convergence zone, allowing underway navigation relative to the buoy. In our demonstration, we showcase the effectiveness of this strategy by successfully conducting over 30 crossings of a river plume front within a 6-h window. The UUV sensors allowed a comprehensive assessment of key front characteristics, including density, velocity, and turbulence. Supplemental drone footage contributed to the overall picture and facilitated the transformation of the dataset into a front-following reference frame. This article provides an in-depth description of the deployment strategy and required postcollection data processing, including frontal crossing detection, the assessment of the frontal orientation from drone footage, and defining the plume bottom boundaries using backscatter intensity contours. Significance Statement: Sampling fast-moving ocean features is challenging and requires flexible tools and creative approaches. In this paper, we present a new method for tracking and studying such features, using a river plume front as an example. Our approach involves using a buoy trapped in the plume front, guiding an uncrewed underwater vehicle (UUV) to follow the front in real time while gathering detailed data. In our test, the UUV crossed the river plume front more than 30 times in 6 h, collecting information on water density, speed, and turbulence. Drone footage added context and helped us analyze the data. This paper explains how we carried out the study and processed the data, including how we detected and mapped the front. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Atmospheric & Oceanic Technology is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=191141359 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1175/JTECH-D-24-0121.1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 1469 Subjects: – SubjectFull: Sampling (Process) Type: general – SubjectFull: Ocean dynamics Type: general – SubjectFull: Buoys Type: general – SubjectFull: Regions of freshwater influence Type: general – SubjectFull: Information processing Type: general – SubjectFull: Drone photography Type: general – SubjectFull: Submersibles Type: general Titles: – TitleFull: High-Resolution Sampling of a River Plume Front with Uncrewed Underwater and Aerial Vehicles. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Piffer-Braga, Agata – PersonEntity: Name: NameFull: MacDonald, Daniel G. – PersonEntity: Name: NameFull: Delatolas, Nikiforos – PersonEntity: Name: NameFull: Goodman, Louis – PersonEntity: Name: NameFull: Huguenard, Kimberly – PersonEntity: Name: NameFull: Whitney, Michael M. – PersonEntity: Name: NameFull: Cole, Kelly – PersonEntity: Name: NameFull: Spicer, Preston IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 07390572 Numbering: – Type: volume Value: 42 – Type: issue Value: 11 Titles: – TitleFull: Journal of Atmospheric & Oceanic Technology Type: main |
| ResultId | 1 |