MétaCan
Menu
Back to cohort
Record W2026950198 · doi:10.1109/oceans.2007.4449132

3D Sidescan with a Small Aperture: Imaging Microbialites at Pavilion Lake

2007· article· en· W2026950198 on OpenAlexafffundabout
Geoff Mullins, John Bird

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space Agency
KeywordsBathymetrySonarGeologyRemote sensingUnderwaterSide-scan sonarBeamwidthMultipath propagationComputer scienceSynthetic aperture sonarMarine engineeringAcousticsSynthetic aperture radarTelecommunicationsOceanographyAntenna (radio)EngineeringPhysics

Abstract

fetched live from OpenAlex

This paper demonstrates the capabilities of a small six element Multi-Angle Swath Bathymetry (MASB) system, deployed in freshwater for the purpose of mapping microbialite structures. It is used to provide both high resolution backscatter imagery, and a bathymetric survey. A 3D sidescan sonar, such as the MASB sonar used in this research, differs from conventional sidescan in that a multiple element receive array is utilized to estimate arrival angles of multiple incoming plane waves. Bathymetry information is calculated using the range of a target and angle of arrival (AOA). The desired signal can be separated from multipath signals which would otherwise corrupt imagery of the bottom. Additionally, a the narrow along track beamwidth and short transmitted pulse length allow for a high resolution image of the lakebed. As the 3D sidescan maintains a small aperture (only slightly larger than sidescan), and uses less channels than multibeam systems (hence fewer electronic components), it is an ideal solution for small platform applications (such as autonomous underwater vehicles AUV) and can be produced less expensively than comparable systems. Surveying can also be performed at a variety of depths (due to multipath elimination), making it possible for a wider range of surveying alternatives such as surface boat mounts (convenient for shallow water), and AUVs. Pavilion Lake, in British Columbia, has been chosen as a survey testbed for two reasons. The primary reason is its importance in analogue space research, having been identified by the Canadian Space Agency as a part of the Canadian Analogue Research Network following the work of [1], which originally reported unique microbialite structures in Pavilion Lake. The second reason is that Pavilion Lake is acoustically interesting. Both the microbialite formations and the soft sediment regions provide for a wide range of acoustically diverse lakebed with mean backscattered signal levels that vary by more than 30 dB. In addition, the complexity of the many mound structures in the lake, provide a survey scenario that is well suited to test the performance of the MASB system under varied geometries. Surveys included in this paper were performed on several occasions between June 2005 and September 2006. Comparing various visual ground truth results (using techniques such as diver observations, remotely operated vehicles and GPS referenced drop camera observations) with backscatter imagery, the distribution of microbialites, as recorded with MASB sonar was examined. Microbialites are located not only around the lake perimeter walls, but also on the slopes of the mound features within the lake as well as sparse isolated patches within the basins. The sonar images of microbialites taken at Pavilion Lake facilitated the discovery of structures with previously unknown morphologies at depths greater than those previously recorded in [1]. Finally, comparisons are made between MASB sonar and other more conventional systems. It is shown that 3D sidescan can be implemented at low cost in comparison to multibeam systems, and provide an alternative to conventional sidescan in many applications, supplying not only high density imagery, but also co-located bathymetry.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.376
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.218
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2007
Admission routes3
Has abstractyes

Explore more

Same topicUnderwater Acoustics ResearchFrench-language works237,207