Literature DB >> 30940026

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

Karsten Klein1,2, Björn Sommer1,3, Hieu T Nim2, Andrea Flack4,5, Kamran Safi4,6, Máté Nagy4,6,5,7, Stefan P Feyer1, Ying Zhang1, Kim Rehberg1, Alexej Gluschkow1, Michael Quetting4, Wolfgang Fiedler4, Martin Wikelski4,6,5, Falk Schreiber1,2,5.   

Abstract

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 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.

Keywords:  animal movement analysis; augmented reality; collective behaviour; immersive analytics; virtual reality

Mesh:

Year:  2019        PMID: 30940026      PMCID: PMC6505562          DOI: 10.1098/rsif.2018.0794

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  20 in total

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Review 4.  ECOLOGY. Terrestrial animal tracking as an eye on life and planet.

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Journal:  IEEE Trans Vis Comput Graph       Date:  2017-01       Impact factor: 4.579

6.  From local collective behavior to global migratory patterns in white storks.

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Journal:  Science       Date:  2018-05-25       Impact factor: 47.728

7.  Facilitating role of 3D multimodal visualization and learning rehearsal in memory recall.

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8.  Analysis and visualization of animal movement.

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Journal:  Biol Lett       Date:  2011-08-24       Impact factor: 3.703

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Journal:  Sci Adv       Date:  2016-01-22       Impact factor: 14.136

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