Mapping fish schools with a high‐resolution multibeam sonar

2006 ◽  
Vol 120 (5) ◽  
pp. 3018-3018
Author(s):  
Mark Trevorrow
Keyword(s):  
High Resolution ◽  
Multibeam Sonar ◽  
Fish Schools

Multibeam sonar image processing and three‐dimensional analysis of fish schools

1998 ◽  
Vol 103 (5) ◽  
pp. 2939-2939 ◽  
Author(s):  
Chafiaa Hamitouche ◽  
Valerie Fracasso ◽  
Carla Scalabrin
Keyword(s):  
Image Processing ◽  
Dimensional Analysis ◽  
Three Dimensional ◽  
Multibeam Sonar ◽  
Fish Schools ◽  
Sonar Image

Management and analysis of high resolution multibeam sonar surveys for geometry characterization of riverbed material

2020 ◽  
Author(s):  
Simone Rover ◽  
Gabriele Avancini ◽  
Alfonso Vitti
Keyword(s):  
High Resolution ◽  
Survey Methods ◽  
High Water ◽  
Quantitative Information ◽  
Water Levels ◽  
Geometric Characterization ◽  
Innovative Technology ◽  
Multibeam Sonar ◽  
Surface Models

<p>The geometric characterization of riverbed material is fundamental piece of information for the management of river basins because it allows, for example, the determination of bed-load and hydrodynamics roughness and the study of geo-morphological phenomenona.<br>However information such the grading curve are not easily achievable by means of traditional field sampling methods, mostly intrusive, and to the hydraulic conditions of rivers that may have high water levels and strong flows.</p><p>Multibeam sonars represent an important alternative to traditional survey methods. Nowadays, thanks to advanced scientific knowledge, it is possible to make full use of an equipment increasingly accurate and precise. State of the art solutions have dimensions compact enough to be installed on remotly piloted vehicles and allow to obtained high resolution digital surface models of river beds. The feasibility of having models of such quality and the possibility to conduct surveys more frequently, allowing the monitoring of sedimentation and erosion phenomena as well as the dynamics of the armouring layer, have motivated the development of advanced and innovative technology to analyse these models.</p><p>The aim of this work is the development of a workflow that provides an effective method to characterize riverbed material. In order to achieve this target we start from an advanced and original survey technique, that allows to obtain high resolution digital surface models, and use an appropriate post-processing procedure.<br>We introduce first some results obtained from the analysis of digital surface models produced in laboratory or relative to well known site. In particular advanced techniques for the study of 3D model and the detection and geometric characterization of forms are investigated.<br>Then we present some data acquired at high resolution (few centimeters) with a multibeam sonar mounted on a remote controlled vessel. Field surveys were conducted in real fluvial environment with the aim of produce qualitative and quantitative information about the surface layer of riverbed.<br>Even considering some sources of uncertainty that may be present from field survey to modeling, the obtained results show how it is possible to identify and geometrically characterize several of the forms present on the surfaces analyzed. </p>

scholarly journals Discriminating between Posidonia oceanica meadows and sand substratum using multibeam sonar

2010 ◽  
Vol 68 (1) ◽  
pp. 12-19 ◽  
Author(s):  
Germana Di Maida ◽  
Agostino Tomasello ◽  
Filippo Luzzu ◽  
Antonino Scannavino ◽  
Maria Pirrotta ◽  
...  
Keyword(s):  
High Resolution ◽  
Classification Accuracy ◽  
Posidonia Oceanica ◽  
Automated Classification ◽  
Multibeam Sonar ◽  
Discriminating Power ◽  
Beam Depth ◽  
Seabed Mapping ◽  
Sandy Substratum

Abstract Di Maida, G., Tomasello, A., Luzzu, F., Scannavino, A., Pirrotta, M., Orestano, C., and Calvo, S. 2011. Discriminating between Posidonia oceanica meadows and sand substratum using multibeam sonar. – ICES Journal of Marine Science, 68: 12–19. High-resolution, multibeam sonar (MBS) (455 kHz) was used to identify two typologies of seabed 8 m deep: Posidonia oceanica meadow and sandy substratum. The results showed that the heterogeneity of the architecture of the P. oceanica canopy and the relatively simple morphology of a sandy substratum can be detected easily by statistical indices such as standard deviation or range-of-beam depth. Based on these indices, an automated classification was performed for seabed mapping. The overall classification accuracy was as high as 99 and 98% in October and January, respectively. The probability that P. oceanica in situ was omitted on the map was <7%, whereas the probability that an area classified as P. oceanica on the map did not correspond to the seagrass in situ was consistently negligible. Based on these results, high-resolution MBS can be considered to be an accurate tool for mapping P. oceanica and sand substrata, and its discriminating power seems to be independent of season (autumn or winter).

Predictive mapping of seabed substrata using high-resolution multibeam sonar data: A case study from a shelf with complex geomorphology

2014 ◽  
Vol 357 ◽  
pp. 37-52 ◽  
Author(s):  
Huang Zhi ◽  
Justy Siwabessy ◽  
Scott L. Nichol ◽  
Brendan P. Brooke
Keyword(s):  
High Resolution ◽  
Predictive Mapping ◽  
Multibeam Sonar

Visualizing Samsonfish (Seriola hippos) with a Reson 7125 Seabat multibeam sonar

2013 ◽  
Vol 70 (3) ◽  
pp. 665-674 ◽  
Author(s):  
Miles J. G. Parsons ◽  
Iain M. Parnum ◽  
Robert D. McCauley
Keyword(s):  
High Resolution ◽  
Western Australia ◽  
Avoidance Behaviour ◽  
Acoustic Backscatter ◽  
Marine Science ◽  
Nearest Neighbour ◽  
Multibeam Sonar ◽  
Neighbour Distance ◽  
Habitat Features

Abstract Parsons, M. J. G., Parnum, I. M., and McCauley, R. D. 2013. Visualizing Samsonfish (Seriola hippos) with a Reson 7125 Seabat multibeam sonar – ICES Journal of Marine Science, 70: 665–674. In Western Australia, aggregations of Samsonfish (Seriola hippos) form each summer to spawn in waters west of Rottnest Island. In this study, a Reson 7125 Seabat multibeam sonar (400 kHz) was pole mounted aboard a 21.6 m vessel, conducting acoustic transects to acquire acoustic backscatter simultaneously from a midwater aggregation of S. hippos and the wreck it surrounded. The processed backscatter produced high-resolution visualizations of both the fish and seabed. During a 15 min period, the centroid of the aggregation moved 91 m around the eastern and northeastern side of the wreck and probably exhibited lateral vessel avoidance behaviour from the survey vessel. Additionally, a northeasterly current at the site was inferred from subtle habitat features, suggesting that at the time of the survey the aggregation preferred to remain upcurrent of the wreck. These findings confirmed that the S. hippos aggregations do not necessarily remain directly above the wrecks and do not always remain sedentary. Aggregation acoustic density packing at the survey site was observed at 12.7 ± 2.4 m3 per fish, equivalent to ∼1.6 ± 0.1 body lengths nearest-neighbour distance.

scholarly journals Kernel methods for the detection and classification of fish schools in single-beam and multibeam acoustic data

2009 ◽  
Vol 66 (6) ◽  
pp. 1130-1135 ◽  
Author(s):  
Bart Buelens ◽  
Tim Pauly ◽  
Raymond Williams ◽  
Arthur Sale
Keyword(s):  
Kernel Methods ◽  
Kernel Method ◽  
Age Groups ◽  
Routine Data ◽  
Acoustic Properties ◽  
Multibeam Sonar ◽  
Single Beam ◽  
Fish Schools ◽  
Acoustic Data

Abstract Buelens, B., Pauly, T., Williams, R., and Sale, A. 2009. Kernel methods for the detection and classification of fish schools in single-beam and multibeam acoustic data. – ICES Journal of Marine Science, 66: 1130–1135. A kernel method for clustering acoustic data from single-beam echosounder and multibeam sonar is presented. The algorithm is used to detect fish schools and to classify acoustic data into clusters of similar acoustic properties. In a preprocessing routine, data from single-beam echosounder and multibeam sonar are transformed into an abstracted representation by multidimensional nodes, which are datapoints with spatial, temporal, and acoustic features as components. Kernel methods combine these components to determine clusters based on joint spatial, temporal, and acoustic similarities. These clusters yield a classification of the data in groups of similar nodes. Including the spatial components results in clusters for each school and effectively detects fish schools. Ignoring the spatial components yields a classification according to acoustic similarities, corresponding to classes of different species or age groups. The method is described and two case studies are presented.

scholarly journals An operational system for automatic school identification on multibeam sonar echoes

2009 ◽  
Vol 66 (5) ◽  
pp. 935-949 ◽  
Author(s):  
Vasilis Trygonis ◽  
Stratis Georgakarakos ◽  
E. John Simmonds
Keyword(s):  
Three Dimensional ◽  
Beam Width ◽  
Multibeam Sonar ◽  
Operational System ◽  
Fish Schools ◽  
Fish School ◽  
School Identification ◽  
Detection And Identification ◽  
Spatio Temporal ◽  
Sonar Echoes

Abstract Trygonis, V., Georgakarakos, S., and Simmonds, E. J. 2009. An operational system for automatic school identification on multibeam sonar echoes. – ICES Journal of Marine Science, 66: 935–949. A system for identifying and tracking fish schools is demonstrated, based on the analysis of multibeam sonar data obtained by a Simrad SP90 long-range sonar. Fish-school detection and identification techniques are similar to those commonly used for vertical echosounders, further enhanced with innovative processing algorithms applied to successive multibeam echograms, increasing the certainty that the identified objects are fish schools. Additionally, analysis of school dynamic parameters facilitates the classification of targets into certain groups, here discriminating the fish aggregating device-natant fish complex from tuna. Statistical analysis of selected tracks quantifies the spatio-temporal variability of the school descriptors, which are used retrospectively to select appropriate analysis thresholds. The algorithms are implemented in an acquisition, visualization, and processing software platform that is flexible regarding sonar characteristics (beam width and number of beams) and can be extended easily to track school echotraces in a three-dimensional mode.

High resolution 3-D shapes of fish schools: A new method to use the water column backscatter from hydrographic MultiBeam Echo Sounders

2016 ◽  
Vol 111 ◽  
pp. 148-160 ◽  
Author(s):  
S. Innangi ◽  
A. Bonanno ◽  
R. Tonielli ◽  
F. Gerlotto ◽  
M. Innangi ◽  
...  
Keyword(s):  
High Resolution ◽  
Water Column ◽  
New Method ◽  
Fish Schools
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