IMOS BA SOOP - Bio Acoustic Data from RV Aurora Australis in the Southern Ocean from the 16th of April 2012 to the 18th of April 2012.

• Other Authors: AODN Data Manager (pointOfContact), AODN Data Manager (distributor), CSIRO Oceans & Atmosphere - Aspendale (hasAssociationWith), CSIRO Oceans & Atmosphere - Hobart (hasAssociationWith), CSIRO Oceans & Atmosphere - IOMRC Crawley (hasAssociationWith), CSIRO Oceans & Atmosphere - St. Lucia (hasAssociationWith), Data Officer (pointOfContact), Data Officer (distributor), Downie, Ryan (pointOfContact), Integrated Marine Observing System (IMOS) (resourceProvider), Kloser, Rudy (hasPrincipalInvestigator)
• Format: Dataset
• Language: unknown
• Published: Australian Ocean Data Network
• Subjects: oceans; Countries | Australia; Global / Oceans | Southern Ocean; ACOUSTIC SCATTERING; EARTH SCIENCE; OCEAN ACOUSTICS; FISH; BIOLOGICAL CLASSIFICATION; ANIMALS/VERTEBRATES; FISHERIES; AGRICULTURE; AGRICULTURAL AQUATIC SCIENCES; Acoustic Equipment/Echo sounders; IMOS Sub-Facility | SOOP-BA | Bio-Acoustic; IMOS Platform | VNAA | Aurora Australis; Ocean Biomass; Micronekton; time; depth; latitude; longitude; mean_volume_backscatter_coefficient; percent_Sv_samples_included_38kHz; mean_cell_height_38kHz; mean_cell_depth_38kHz; mean_volume_backscatter_including_bad_data_38kHz; aurora australis; Southern Ocean
• Online Access: https://researchdata.edu.au/imos-ba-soop-april-2012/693330

Statement: I. Data collection: Vessel calibration: Vessels are calibrated according to the procedures recommended in the ICES CRR 144 document by (Foote 1987). In the case of ES60 systems, the calibration data is pre-processed to eliminate the possibility of bias of up to +/- 0.5 dB due to the systematic triangle wave error that is embedded in the ES60 data (Ryan and Kloser 2004). This triangle wave error can be significant for calibration data, but for field data it averages to zero over long periods and is not considered a significant source of error. Hence processing to eliminate the triangle wave error from field data is not done. At a minimum vessels are ideally calibrated annually but logistics may dictate different time intervals. II. Data management: In-house tools have been developed to assist with data management and help identify and prioritise subsets of data for post-processing. The data management tool borrows from the open-source multi-beam processing software MB-System (http://grass.osgeo.org/wiki/MB-System) approach by generating from each of the acoustic raw files, a corresponding inf file. The inf file is in text format and contains the temporal and geographic extent of the associated raw file. The inf files are created during a data registration process using the tool ES60_register.jar. User defined metadata can be included during the registration process (e.g voyage name, vessel name). During registration metadata can be automatically extracted from the binary raw files and included in the inf file (e.g. Echo sounder serial number). The inf files can be visualised as geo-referenced rectangle blocks using our open-source software Dataview.jar. Dataview.jar has the tools to select blocks of inf files by defining time-windows, spatial extents, and keywords or a combination of these. III. Data processing: Data processing is carried out via the following steps: 1. Generate a list of on-transit acoustic files to process using Dataview’s visualisation of inf files. 2. Using Myriax’s Echoview ...