Fly with the flock: immersive solutions for animal movement visualization and analytics

Karsten Klein, Björn Sommer, Hieu T. Nim, Andrea Flack, Kamran Safi, Máté Nagy, Stefan P. Feyer, Ying Zhang, Kim Rehberg, Alexej Gluschkow, Michael Quetting, Wolfgang Fiedler (+2 others)
2019 Journal of the Royal Society Interface  
Understanding the movement of animals is important for a wide range of scientific interests including migration, disease spread, collective movement behaviour and analysing motion in relation to dynamic changes of the environment such as wind and thermal lifts. Particularly, the three-dimensional (3D) spatial-temporal nature of bird movement data, which is widely available with high temporal and spatial resolution at large volumes, presents a natural option to explore the potential of immersive
more » ... analytics (IA). We investigate the requirements and benefits of a wide range of immersive environments for explorative visualization and analytics of 3D movement data, in particular regarding design considerations for such 3D immersive environments, and present prototypes for IA solutions. Tailored to biologists studying bird movement data, the immersive solutions enable geo-locational time-series data to be investigated interactively, thus enabling experts to visually explore interesting angles of a flock and its behaviour in the context of the environment. The 3D virtual world presents the audience with engaging and interactive content, allowing users to 'fly with the flock', with the potential to ascertain an intuitive overview of often complex datasets, and to provide the opportunity thereby to formulate and at least qualitatively assess hypotheses. This work also contributes to ongoing research efforts to promote better understanding of bird migration and the associated environmental factors at the global scale, thereby providing a visual vehicle for driving public awareness of environmental issues and bird migration patterns.
doi:10.1098/rsif.2018.0794 pmid:30940026 pmcid:PMC6505562 fatcat:7dieshmrtndljb6axobzphvwae