Skip to content

emiliom/echopype

 
 

Repository files navigation

image

Documentation Status

image

Echopype

Echopype is a package built for enhancing the interoperability and scalability in ocean sonar data processing. These data are widely used for obtaining information about the distribution and abundance of marine animals, such as fish and krill. Our ability to collect large volumes of sonar data from a variety of ocean platforms has grown significantly in the last decade. However, most of the new data remain under-utilized. echopype aims to address the root cause of this problem - the lack of interoperable data format and scalable analysis workflows that adapt well with increasing data volume - by providing open-source tools as entry points for scientists to make discovery using these new data.

Installaion and Usage

Echopype currently supports file conversion and computation of data produced by:

  • Simrad EK60 echosounder (.raw files)
  • ASL Environmental Sciences AZFP echosounders (.01A files)

The file conversion functionality converts data stored in manufacturer-specific binary formats into a standardized netCDF files, based on which all subsequent computations are performed. The data processing routines include calibration (instrument-specific), noise removal, and mean volume backscattering strength (MVBS) calculation.

Check out the echopype documentation for details on installation and usage!

License

Echopype is licensed under the open source Apache 2.0 license.

Wu-Jung Lee (@leewujung) and Kavin Nguyen (@ngkavin) are the primary developers of this project.

Other contributors include: Valentina Staneva (@valentina-s), Frederic Cyr (@cyfr0006), Sven Gastauer (@SvenGastauer), Marian Peña (@marianpena), Mark Langhirt (@bnwkeys), Erin LaBrecque (@erinann), Emma Ozanich (@emma-ozanich), Aaron Marburg (@amarburg)


Copyright (c) 2018--, echopype Developers.

About

Enhancing the interoperability and scalability in analyzing ocean sonar data

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Jupyter Notebook 97.7%
  • Python 2.3%