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A gaussian mixture model to separate birds and insects in single-polarization weather radar data

Nussbaumer, Raphaël; Schmid, Baptiste; Bauer, Silke; Liechti, Felix
Magazine
Remote Sens. (Remote Sensing)
Langue
eng
Année de publication
2021
Zenodo open repository

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Résumé

Recent and archived data from weather radar networks are extensively used for the quantification of continent-wide bird migration patterns. While the process of discriminating birds from weather signals is well established, insect contamination is still a problem. We present a simple method combining two Doppler radar products within a Gaussian mixture model to estimate the proportions of birds and insects within a single measurement volume, as well as the density and speed of birds and insects. This method can be applied to any existing archives of vertical bird profiles, such as the European Network for the Radar surveillance of Animal Movement repository, with no need to recalculate the huge amount of original polar volume data, which often are not available.

Keywords: migration ecology; classification; ornithology; Gaussian mixture model; vertical profile; ecological modelling; aeroecology

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