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

Corresponding Author:[email protected]

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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.
Nov 2021Published in Ecology and Evolution volume 11 issue 22 on pages 16214-16227. 10.1002/ece3.8302