Robust Algorithms for Drone-Assisted Monitoring of Big Animals in Harsh Conditions of Siberian Winter Forests: Recovery of European elk ( Alces alces ) in Salair Mountains

• Published in: Animals
• Main Authors: Alexander Prosekov, Anna Vesnina, Victor Atuchin, Aleksandr Kuznetsov
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2022
• Subjects: large animals; computer technology; UAV; comparison of accounting methods; nature reserve; Veterinary medicine; SF600-1100; Zoology; QL1-991; Alces alces; Siberia
• Online Access: https://doi.org/10.3390/ani12121483; https://doaj.org/article/28472ad73569415dbbf9b97b37d9a102

There are two main reasons for monitoring the population of forest animals. First, regular surveys reveal the real state of biodiversity. Second, they guarantee a prompt response to any negative environmental factor that affects the animal population and make it possible to eliminate the threat before any permanent damage is done. The research objective was to study the potential of drone planes equipped with thermal infrared imaging cameras for large animal monitoring in the conditions of Siberian winter forests with snow background at temperatures −5 °C to −30 °C. The surveyed territory included the Salair State Nature Reserve in the Kemerovo Region, Russia. Drone planes were effective in covering large areas, while thermal infrared cameras provided accurate statistics in the harsh winter conditions of Siberia. The research featured the population of the European elk ( Alces alces ), which is gradually deteriorating due to poaching and deforestation. The authors developed an effective methodology for processing the data obtained from drone-mounted thermal infrared cameras. The research provided reliable results concerning the changes in the elk population on the territory in question. The use of drone planes proved an effective means of ungulate animal surveying in snow-covered winter forests. The designed technical methods and analytic algorithms are cost-efficient and they can be applied for monitoring large areas of Siberian and Canadian winter forests.