Location Analysis: Difference between revisions

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Below you will find a brief outline of each technique and a link to a description of how it is implemented in Ranges.
Below you will find a brief outline of each technique and a link to a description of how it is implemented in Ranges.
==Inter-location Measures==
==Convex Polygons==
==Concave Polygons==
==Ellipses==
==Clusters==
==Harmonic Mean Contours==
==Kernel Contours==
==Midline Analyses (Interlocation, Linear Ranges and Clusters)==

Revision as of 07:19, 14 October 2014

This panel provides a number of analyses of location data, which are used either to provide simple inter-location measures, including dispersal detection, or to estimate home ranges. A wide variety of different methods of range analysis have been published. Ranges implements those that have been used to produce refereed publications beyond a first description, including convex polygons (sometimes called minimum area convex polygons, MCPs or MAPs), #Concave Polygons,concave polygons (with restricted edges), polygons in #Clusters,clusters, #Ellipses, ellipses and contouring from #Harmonic Means,harmonic means and other density #Kernels,kernels. Grid cells may be plotted by selecting options within #Concave Polygons,concave polygons.

The pros and cons of these different techniques are discussed in more detail in the Review Of Home Range Analyses, review of home range analyses and for a more comprehensive recent review, see “A Manual for Wildlife Radio Tagging” (Kenward 2001) and Kenward et al. 2001.

Below you will find a brief outline of each technique and a link to a description of how it is implemented in Ranges.


Inter-location Measures

Convex Polygons

Concave Polygons

Ellipses

Clusters

Harmonic Mean Contours

Kernel Contours

Midline Analyses (Interlocation, Linear Ranges and Clusters)