Time-Space Cloud with R


Here comes another option to analyze a TimeSpace-Track with R. A lattice cloud plots every recorded trackpoint into a 3d-time-space-cube. As the data (planar point pattern) is marked with the daytime, cluster of everyday routines become visible.

Here the direct comparison between a function of density and the time-space-cloud.

Time space Clowd

spatstat density plot

Code example:

cloud(time_hours ~ PPP_selection$x * PPP_selection$y, data = daten, zlim = c(23,0), xlim = c(653000,643000), screen = list(z = 160, x = 120), panel.aspect = 0.75, xlab = “Longitude”, ylab = “Latitude”, zlab = “Time”, scales = list(z = list(arrows = FALSE, distance = 2), x = list(arrows =FALSE, distance = 2), y = list(arrows = FALSE, distande = 2)),)

This examle is inspired by: http://lmdvr.r-forge.r-project.org/ (Figure 6.2)


2 Responses to “Time-Space Cloud with R”

  1. andrew white Says:

    Very interested in the TimeSpace Cloud for health services research. I want to repeat uyour data plot first: what is the source of the dataset: daten? Thanks, AW.

  2. bene Says:

    I’m not sure if I got your question right: In this case the option “data=” is not really needed, because I feed the function with explicid variable names (time_hours, PPP_selection$x …). PPP_selection$x and PPP_selection$y are UTM converted Trackpoints recorded by a gps-tracker. Perhaps the webpage http://lmdvr.r-forge.r-project.org/ and the helpfiles to the Lattice-Function “cloud()” may help you with your project.

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