Studies of habitat-related behaviour of mammals are time-consuming. This study aims to develop a model for monitoring the behaviour of mammals in different habitat types using drones mounted with thermal cameras in combination with a YOLO object detection model. Red deer (Cervus elaphus) and fallow deer (Dama dama) were used as model species. The data were collected in the nature reserve, Hanstholm, Northern Denmark. The aim is to develop an AI model capable of distinguishing between four behaviours, “foraging”, “locomoting”, “lying” and “standing”, allowing for insights into the rumination and foraging cycle of the two species. At the same time, the behaviour was linked to habitat types by geocoding individuals. The method developed in this study proved to be time-efficient and provided information about how the two deer species used vegetation types and interspecific interaction between the two species. Technical challenges were to follow individuals and the possibility of missing cyclical behaviour. It was found that the degree to which the ungulates actively foraged was significantly different between the two species and that they were clearly geographically separated within the study area.


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    Titel :

    The Use of Open Vegetation by Red Deer (Cervus elaphus) and Fallow Deer (Dama dama) Determined by Object Detection Models


    Beteiligte:
    Lasse Lange Jensen (Autor:in) / Cino Pertoldi (Autor:in) / Sussie Pagh (Autor:in)


    Erscheinungsdatum :

    2025




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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