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Drones, automatic counting tools and artificial neural networks in wildlife population censusing
  • Dominik Marchowski
Dominik Marchowski
Polish Academy of Sciences
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Abstract

1. The use of a drone to count the flock sizes of 33 species of waterbirds during the breeding and non-breeding periods was investigated. 2. In 96% of 343 cases, drone counting was successful. 18.8% of non-breeding birds and 3.6% of breeding birds exhibited adverse reactions: in the former, the birds were flushed, whereas the latter attempted to attack the drone. 3. The automatic counting birds was best done with the microbiology software - ImageJ / Fiji: the average bird counting rate was 100 birds in 82 seconds. 4. Machine learning using neural network algorithms proved to be an effective and fast way of counting birds – 100 birds in 23 seconds. However, as the preparation of images and machine learning time are time-consuming, this method is recommended only for large data sets and large bird assemblages. 5. The responsible study of wildlife using a drone should only be carried out by persons experienced in the biology and behaviour of the animals concerned.