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

Zitieren Sie bitte immer diese 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.zeige mehrzeige weniger

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Metadaten
Autor(en): Jakob Schwalb‐WillmannORCiD, Ruben Remelgado, Kamran Safi, Martin WegmannORCiD
URN:urn:nbn:de:bvb:20-opus-214856
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Philosophische Fakultät (Histor., philolog., Kultur- und geograph. Wissensch.) / Institut für Geographie und Geologie
Sprache der Veröffentlichung:Englisch
Titel des übergeordneten Werkes / der Zeitschrift (Englisch):Methods in Ecology and Evolution
Erscheinungsjahr:2020
Band / Jahrgang:11
Heft / Ausgabe:5
Erste Seite:664
Letzte Seite:669
Originalveröffentlichung / Quelle: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
Allgemeine fachliche Zuordnung (DDC-Klassifikation):5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Freie Schlagwort(e):animal tracking; animation; data visualization; movement data; movement ecology; spatio‐temporal data
Datum der Freischaltung:19.04.2021
Lizenz (Deutsch):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International