moveVis provides tools to visualize movement data (e.g. from GPS tracking) and temporal changes of environmental data (e.g. from remote sensing) by creating video animations. It works with
raster class inputs and turns them into
ggplot2 frames that can be further customized.
gifski (wraping the gifski cargo crate) and
av (binding to FFmpeg) to render frames into animated GIF or video files.
Figure 1: Example movement tracks nearby Lake of Constance on top of a OSM watercolor and a mapbox satellite base map
Figure 2: Example movement tracks nearby Lake of Constance and a gradient base layer faded over time
With version 0.10.0, the package has been rewritten from the ground up with the goal to make it easier to customize the appearance of movement animations. Thus, the logic of the package, its functions and their syntax have changed.
moveVis 0.10.0 (stable) can be installed from CRAN:
The development version can be installed from GitHub:
Code written for
moveVis version <=0.9.9 will not work with newer versions, but it is quite simple and thus highly recommended to switch to the new syntax due to a variety of advantages.
moveVis version <=0.9.9 can still be downloaded here and installed manually:
setwd("your/download/directory") install.packages("moveVis-0.9.9.tar.gz", repos = NULL)
moveVis includes the following functions, sorted by the order they would be applied to create an animation from movement and environmental data:
Preparing movement tracks
moveStackobject. This is useful if you do not usually work with the
moveclasses and your tracks are present as
align_move()aligns single and multi-individual movement data to a uniform time scale with a uniform temporal resolution needed for creating an animation from it. Use this function to prepare your movement data for animation depending on the temporal resolution that suits your data.
moveStackby a given time span. This is useful if you want to create a movement animation of only a temporal subset of your data, e.g. a particular day.
get_maptypes()returns a character vector of available map types that can be used with
moveVissupports OpenStreetMaps and Mapbox basemap imergay. Alternatively, you can provide custom imagery to
frames_spatial()creates a list of
ggplot2maps displaying movement. Each object represents a single frame. Each frame can be viewed or modified individually. The returned list of frames can be animated using
frames_graph()creates a list of
ggplot2graphs displaying movement-environment interaction. Each object represents a single frame. Each frame can be viewed or modified individually. The returned list of frames can be animated using
ggplot2functions (e.g. to add layers such as points, polygons, lines, or to change scales etc.) to the animation frames created with
frames_graph(). Instead of creating your own
ggplot2functions, you can use one of the other
add_labels()adds character labels such as title or axis labels to animation frames created with
add_scalebar()adds a scalebar to the animation frames created with
add_northarrow()adds a north arrow to the animation frames created with
add_progress()adds a progress bar to animation frames created with
add_timestamps()adds timestamps to animation frames created with
add_text()adds static or dynamically changing text to the animation frames created with
add_colourscale()adjusts the colour scales of the animation frames created with
frames_spatial()and custom map imagery using the
join_frames()side-by-side joins the
ggplot2objects of two or more frames lists of equal lengths into a single list of
ggplot2objects per frame using
cowplot::plot_grid. This is useful if you want to side-by-side combine spatial frames returned by
frames_spatial()with graph frames returned by
Animating frames (as GIF or video)
suggest_formats()returns a selection of suggested file formats that can be used with
animate_frames()on your system.
animate_frames()creates an animation from a list of frames computed with
Viewing movement tracks
view_spatial()displays movement tracks on an interactive
The following example shows how to make a simple animation using a default base map by first aligning your movement data to a uniform time scale, creating a list of
ggplot2 frames and turning these frames into an animated
library(moveVis) library(move) data("move_data") # move class object # if your tracks are present as data.frames, see df2move() for conversion # align move_data to a uniform time scale move_data <- align_move(move_data, res = 240, digit = 0, unit = "secs") # create spatial frames with a OpenStreetMap watercolour map frames <- frames_spatial(move_data, path_colours = c("red", "green", "blue"), map_service = "osm", map_type = "watercolor", alpha = 0.5) frames[] # preview one of the frames # animate frames animate_frames(frames, out_file = "/full/path/to/example_1.gif")
You can find detailed code examples on how to use
Example 4: Custom base maps from raster data (to be added soon)
Example 5: Interaction graphs (to be added soon)
Example 6: Joining frames side by side (to be added soon)
moveVis code snippets, addressing specific issues or questions, could also be helpful to you:
Features to be added
Things and features that should be added in future versions of
moveVis (feel free to contribute to this list using a pull request):
- "keep tracks" setting to force paths to not disappear
- follow population mode
- follow individual mode
- day-/night-time visualization
- 3D animations, e.g. for including altitude data
The Department of Remote Sensing of the University of Würzburg has developed other R packages that might interest you:
- getSpatialData, a package to query, preview and download satellite data,
- RStoolbox, a package providing a wide range of tools for every-day remote sensing processing needs,
- rsMove, a package providing tools to query and analyze movement data using remote sensing.
For other news on the work at at the Department of Remote Sensing of the University of Würzburg, click here.
This initiative is part of the Opt4Environment project and was funded by the German Aerospace Center (DLR) on behalf of the Federal Ministry for Economic Affairs and Energy (BMWi) with the research grant 50 EE 1403.