With the rgl package its possibele to interact with the 3d visualization of the timespace tracks. Code example: plot3d(lon,lat,timedate, xlim=range(lon), ylim=range(lat), zlim=range(timedate), ticktype=”detailed”, xlab=”longitudeR...
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. Code example: cloud(time_hours ~ PPP_selection$x...
Beside the visualisation of TimeSpace Tracks, I’m trying to find a way to analyze GPX-Tracks with statistical software. This are the first results with R (The R Project for Statistical Computing): ^This graph is a result of the analysis with the package trip (Spatial analysis of animal track data). Unfortunatelly i’m do not understand...