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Processing-and-analysis-of-large-ADCP-datasets
This document will guide you through the steps necessary to process and analyse both vessel mounted (VM-ADCP) and lowered acoustic doppler current profilers (L-ADCP). Both are complex data sources that contain a lot of noise and potential biases, but dont despair, with todays programms and code packages anyone can work with this data and produce meaningfull results.Tindeq-Progressor-climbing-strength-test-server
A python and bokeh application that creates a user interface to run climbing strength tests, that can store, visualize and send resultsPython-Audio-Spectrogram-Explorer
A program to visualize audio files as spectrograms and log annotations. Developed to analyse marine mammal recordings, but can be used for many things.ADCP_bottom_detection
An algorithm that detects the bottom in ADCP backscatter data as part of a Matlab package for ADCP processingpython-acoustic-backscatter-analysis
a collection of python scripts to analyse acoustic backscatter data from moored or vessel mounted echosounderskrillscan
Python based software to automatically analyse and transfer echosounder dataVector-interpolation
How to interpolate vector data / current fields from sparse observationsMarine-mammal-call-detection-using-spectrogram-shape-matching
A detection algorithm to find and classify audio signals using a shape templateProcessing-ADCP-data-from-IMR-vessels
A tutorial that shows how to find and post-process vessel mounted ADCP data from IMR vessels using the CODAS environment.Analyzing-ambient-sound-recordings-from-Aural-M2-recorders-with-python
Analyzing ambient sound recordings from Aural M2 recorders with pythonTransmission-loss-modeling-with-Bellhop-and-Matlab
A collection of matlab scripts toacoustic_recorder_detection_range_modeling
Modeling the detection range of underwater recorders - using python, acoustic propagation models and ocean reanalysis dataLove Open Source and this site? Check out how you can help us