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moveVis: Animating movement trajectories in synchronicity with static or temporally dynamic environmental data in R

Please always quote using this URN: urn:nbn:de:bvb:20-opus-214856
  • Visualizing movement data is challenging: While traditional spatial data can be sufficiently displayed as two‐dimensional plots or maps, movement trajectories require the representation of time in a third dimension. To address this, we present moveVis, an R package, which provides tools to animate movement trajectories, overlaying simultaneous uni‐ or multi‐temporal raster imagery or vector data. moveVis automates the processing of movement and environmental data to turn such into an animation. This includes (a) the regularization ofVisualizing movement data is challenging: While traditional spatial data can be sufficiently displayed as two‐dimensional plots or maps, movement trajectories require the representation of time in a third dimension. To address this, we present moveVis, an R package, which provides tools to animate movement trajectories, overlaying simultaneous uni‐ or multi‐temporal raster imagery or vector data. moveVis automates the processing of movement and environmental data to turn such into an animation. This includes (a) the regularization of movement trajectories enforcing uniform time instances and intervals across all trajectories, (b) the frame‐wise mapping of movement trajectories onto temporally static or dynamic environmental layers, (c) the addition of customizations, for example, map elements or colour scales and (d) the rendering of frames into an animation encoded as GIF or video file. moveVis is designed to display interactions and concurrencies of animal movement and environmental data. We present examples and use cases, ranging from data exploration to visualizing scientific findings. Static spatial plots of movement data disregard the temporal dimension that distinguishes movement from other spatial data. In contrast, animations allow to display relocation in both time and space. We deem animations a powerful way to visually explore movement data, frame analytical findings and display potential interactions with spatially continuous and temporally dynamic environmental covariates.show moreshow less

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Metadaten
Author: Jakob Schwalb‐WillmannORCiD, Ruben Remelgado, Kamran Safi, Martin WegmannORCiD
URN:urn:nbn:de:bvb:20-opus-214856
Document Type:Journal article
Faculties:Philosophische Fakultät (Histor., philolog., Kultur- und geograph. Wissensch.) / Institut für Geographie und Geologie
Language:English
Parent Title (English):Methods in Ecology and Evolution
Year of Completion:2020
Volume:11
Issue:5
First Page:664
Last Page:669
Source:Methods in Ecology and Evolution 2020, 11(5):664-669. DOI: 10.1111/2041-210X.13374
DOI:https://doi.org/10.1111/2041-210X.13374
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Tag:animal tracking; animation; data visualization; movement data; movement ecology; spatio‐temporal data
Release Date:2021/04/19
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International