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List of contents
Introduction in R. basic data objects (vector, data.frame, array, martix, factor). Overview of "sp", "adeHabitat" and "move" objects and supplementary libraries. Methods of data collection and implications for analysis. Tracking technologies. Problem of projections. Problem of scaling. Trajectory centered analysis. Geometry of trajectories. Simulation of random trajectories. Statistical approaches in trajectory based analysis. Classical approaches. State-Space models. Computer-intense models. Segmentation of trajectories. Corridor functions. Discerning behavioural changes. Area centered analysis. MCP, Kernel, Brownian Bridges: From trajectories to utilisation distributions. Statistical approaches in area based analysis. Methods of calculating UD overlap. Movement in context. Geoinformation (Remote sensing, rasters and vector data). Visualisation of contextual information. Accessing spatio-temporal data. Contextual annotation of trajectories and area composition. Raster resolution and UD calculation. Compositional analysis (comparing available vs. used resources). Species distribution models in movement analysis. Visualisation of animal movement. General mapping of spatio-temporal data. Time-Space Cubes -> rgl. Plotting of additional information. Animations. The future of animal movement analysis. Additional sensors.
Summary
Movement ecology is a deeply interdisciplinary and prolific area of research, requiring skills that combine information technology, data mining, statistics and mathematics, geography, remote sensing, and ecology. The authors elaborate on methods to analyze and visualize animal movement using the software package R. The book will first concentrate on the analysis of trajectories, the paths of individual animals, looking at the geometry and characteristics that can be derived from single trajectories.
