Don’t work too hard: Subsampling leads to efficient analysis of large acoustic datasets
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Help
Clear All

Query Builder

Query box

Help
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Don’t work too hard: Subsampling leads to efficient analysis of large acoustic datasets

Filetype[PDF-6.04 MB]


Select the Download button to view the document
This document is over 5mb in size and cannot be previewed
Details You May Also Like

Details:

  • Journal Title:
    Fisheries Research
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    Echo-integration measurements have been traditionally made from dedicated fisheries survey vessels, but extensive measurements from moorings, autonomous vehicles, and fishing vessels are increasingly available. Processing these data by traditional means developed for well-staffed fisheries surveys can be prohibitively time-consuming, which has limited their use. Automated processing methods exist to efficiently handle these large datasets; however, as compared to post-processing by trained analysts, these methods require substantial expertise and methodological development, and they often produce less certain results. Here, we evaluate the use of subsampling, which takes advantage of the spatial correlation common in many fish populations, to improve the efficiency of traditional processing methods while retaining a high level of precision. We subsampled data from an eastern Bering Sea walleye pollock (Gadus chalcogrammus) acoustic-trawl survey and compared estimates of pollock backscatter from subsamples to those from the full survey. Over a survey-wide scale, processing < 5% of the data resulted in estimates within 5% of those from processing the full survey. This suggests that in some applications there may be diminishing returns associated with exhaustively processing large spatially correlated datasets. We present an example that applies this simple approach by subsampling archived echosounder data from chartered fishing vessels to prioritize the areas surveyed in future surveys, which would not have been feasible without subsampling. When averaged values over large scales (e.g. over a survey domain) are required, precise echo integration estimates can be obtained with modest effort by processing relatively small subsamples of a dataset.
  • Keywords:
  • Source:
    Fisheries Research, 219: 105323
  • DOI:
  • Document Type:
    Journal Article
  • Rights Information:
    Accepted Manuscript
  • Compliance:
    Submitted
  • Main Document Checksum:
  • Download URL:
  • File Type:

Supporting Files

  • No Additional Files

More +

You May Also Like

Checkout today's featured content at repository.library.noaa.gov

Version 3.26