Echostack: A flexible and scalable open-source software suite for echosounder data processing

Details

• Journal Title:
  Proceedings of the Python in Science Conference
• Personal Author:
  Lee, Wu-Jung ; Staneva, Valentina ; Setiawan, Landung “Don” ; Mayorga, Emilio ; Tuguinay, Caesar ; Butala, Soham ; Lucca, Brandyn ; Lei, Dingrui
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; Ocean Exploration Program
• Description:
  Water column sonar data collected by echosounders are essential for fisheries and marine ecosystem research, enabling the detection, classification, and quantification of fish and zooplankton from many different ocean observing platforms. However, the broad usage of these data has been hindered by the lack of modular software tools that allow flexible composition of data processing workflows that incorporate powerful analytical tools in the scientific Python ecosystem. We address this gap by developing Echostack, a suite of open-source Python software packages that leverage existing distributed computing and cloud-interfacing libraries to support intuitive and scalable data access, processing, and interpretation. These tools can be used individually or orchestrated together, which we demonstrate in example use cases for a fisheries acoustic-trawl survey.
• Keywords:
  FY21 NOFO
• Source:
  Proceedings of the Python in Science Conference (2024)
• DOI:
  https://doi.org/10.25080/WXRH8633
• ISSN:
  2575-9752
• Format:
  pdf
• Publisher:
  SciPy
• Document Type:
  Journal Article
• Funding:
  Grant no. NA21OAR0110201-T1-01
• License:
  https://creativecommons.org/licenses/by/4.0/
• Rights Information:
  CC BY
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:b4cb576e6ed1e872a7a0bf90aca88128b0ebc765ccbc10d0ba9d856c1947c16f47c27e4eab437d751630830b57f8ce46626b8aaf16e6bae8c8cb528c2483c0f3
• Download URL:
  https://repository.library.noaa.gov/view/noaa/71895/noaa_71895_DS1.pdf
• File Type:
  [PDF - 4.32 MB ]