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Acoustic monitoring is a powerful technique for learning about the ecology of bats. Bat recorders provide continuous registration of bat activity by recording echolocation calls of passing bats. Since the bat calls are highly reliable taxonomic features, the acquired data can be used to estimate diversity and relative abundance of the occurring species. The generated data provides a basis for ecological and behavioral research of the bat species occurring in our coastal and marine areas. BatSounds is an open source repository that contains scripts to work with BatCorder data and BatCorder devices. The repository contains two scripts that are useful to process and send the audio data retrieved by ecoObs Batcorders (https://ecoobs.com/): - Raw_to_wav is a python script that adds a header to raw audio files from the BatCorder so it can more easily be used by different softwares as a wav file. - beaglebone_batcorder is a bash-script to run on a Beaglebone Black minicomputer connected to a BatCorder. It copies the data from the BatCorder daily to its own SD card and sends it to an FTP server over Ethernet. It allows for remote data transfer and memory management of the BatCorder. LifeWatch Belgium has currently four ecoObs BatCorders installed. You can find more information here: https://lifewatch.be/en/sensor-network-bat-detection
pyhydrophone is an open-source Python package that has been developed to ease the import of underwater sound data recorded with a hydrophone to python, so postprocessing and AI can be easily performed on the data afterwards. Different recorders can be added with their different way of reading metadata, so the users do not have to worry about the format but just about the outcome.
pyporcc is an open-source Python package developed to detect and classify harbour porpoise’s clicks in audio files using the PorCC algorithm and offering the possibility to create new clicks classifiers. It provides a framework to train different models such as Support Vector Machines, Linear Support Vector Machines, Random Forest and K-Nearest Neighbour that classify sound clips in Noise, and Low-Quality and High-Quality harbour porpoises’ clicks. The algorithm from PAMGuard to detect possible clicks clips is also implemented.
The package lwdataexplorer retrieves biodiversity, environmental or genetic data from the projects supported by LifeWatch Belgium. These data are also available to explore and download through the LifeWatch Data Explorer: an R Shiny application that allows you to check and download data from your browser.