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      The potential of using Unmanned Aerial Vehicles (UAVs) for precision pest control of possums (Trichosurus vulpecula)

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      Rethinking Ecology
      Pensoft Publishers

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          High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision

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            UAVs challenge to assess water stress for sustainable agriculture

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              Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation

              Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.
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                Author and article information

                Journal
                Rethinking Ecology
                ReEco
                Pensoft Publishers
                2534-9260
                October 23 2017
                October 23 2017
                : 2
                : 27-39
                Article
                10.3897/rethinkingecology.2.14821
                0192a047-5622-47e3-a462-498eb633ba0a
                © 2017

                http://creativecommons.org/licenses/by/4.0/

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