eRTG3D
Empirically Informed Random Trajectory Generation in 3-D
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.
- Version0.7.0
- R version≥ 3.5.0
- LicenseGPL-3
- Needs compilation?No
- eRTG3D citation info
- Last release02/25/2022
Documentation
- VignetteIncluded example data sets
- VignetteStandard workflow of the eRTG3D
- VignetteVisualization of trajectories
- VignetteVerification of results
- VignetteParallel computation
- VignetteCoordinate reference system transformations in 3-D
- VignetteLinkage to the 'sf' package
- VignetteTrajectory simulations in 2-D
- VignettePoint cloud analysis
- MaterialREADME
- MaterialNEWS
Team
Merlin Unterfinger
Kamran Safi
Show author detailsRolesContributor, Thesis advisorGeorge Technitis
Show author detailsRolesContributor, Thesis advisorRobert Weibel
Show author detailsRolesThesis advisor
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- Depends1 package
- Imports7 packages
- Suggests9 packages