plot3d.multiplot

plotlist

cols

<p>a matrix specifying the layout. If present, <code>cols</code> is ignored.</p>

layout

<p>If the layout is something like <code>matrix(c(1,2,3,3), nrow=2, byrow=TRUE)</code>,
then plot 1 will go in the upper left, 2 will go in the upper right, and
3 will go all the way across the bottom.</p>

Creates realistic random trajectories in a 3-D space between two given fix points, so-called conditional empirical random walks (CERWs). The trajectory generation is based on empirical distribution functions extracted from observed trajectories (training data) and thus reflects the geometrical movement characteristics of the mover. A digital elevation model (DEM), representing the Earth's surface, and a background layer of probabilities (e.g. food sources, uplift potential, waterbodies, etc.) can be used to influence the trajectories.
Unterfinger M (2018). "3-D Trajectory Simulation in Movement Ecology: Conditional Empirical Random Walk". Master's thesis, University of Zurich. <https://www.geo.uzh.ch/dam/jcr:6194e41e-055c-4635-9807-53c5a54a3be7/MasterThesis_Unterfinger_2018.pdf>.
Technitis G, Weibel R, Kranstauber B, Safi K (2016). "An algorithm for empirically informed random trajectory generation between two endpoints". GIScience 2016: Ninth International Conference on Geographic Information Science, 9, online. <doi:10.5167/uzh-130652>.

Merlin Unterfinger

eRTG3D

Empirically Informed Random Trajectory Generation in 3-D

Kamran Safi

George Technitis

Robert Weibel

plot3d.multiplot function

Multiple plot function for ggplot objects — plot3d.multiplot

Multiple plot function for ggplot objects

plot3d.multiplot: Multiple plot function for ggplot objects

Description

Usage

Arguments

Value

Examples