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The concept of animals' trajectories from a data analysis perspective.
- Source :
- Ecological Informatics; Jan2009, Vol. 4 Issue 1, p34-41, 8p
- Publication Year :
- 2009
-
Abstract
- Abstract: The Global Positioning System (GPS) has been increasingly used during the past decade to monitor the movements of free-ranging animals. This technology allows to automatically relocate fitted animals, which often results into a high-frequency sampling of their trajectory during the study period. However, depending on the objective of trajectory analysis, this study may quickly become difficult, due to the lack of well designed computer programs. For example, the trajectory may be built by several “parts” corresponding to different behaviours of the animal, and the aim of the analysis could be to identify the different parts, and thereby the different activities, based on the properties of the trajectory. This complex task needs to be performed into a flexible computing environment, to facilitate exploratory analysis of its properties. In this paper, we present a new class of object of the R software, the class “ltraj” included in the package adehabitat, allowing the analysis of animals'' trajectories. We developed this class of data after an extensive review of the literature on the analysis of animal movements. This class of data facilitates the computation of descriptive parameters of the trajectory (such as the relative angles between successive moves, distance between successive relocations, etc.), graphical exploration of these parameters, as well a numerous tests and analyses developed in the literature (first passage time, trajectory partitioning, etc.). Finally, this package also contains numerous examples of animal trajectories, and a working example illustrating the use of the package. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 15749541
- Volume :
- 4
- Issue :
- 1
- Database :
- Supplemental Index
- Journal :
- Ecological Informatics
- Publication Type :
- Academic Journal
- Accession number :
- 36567910
- Full Text :
- https://doi.org/10.1016/j.ecoinf.2008.10.002