adehabitatHR (version 0.4.22)

MCHu: The Class "MCHu": Managing Home Ranges Built by Multiple Convex Hulls

Description

The class "MCHu" is designed to store home ranges built by multiple convex hulls, for example built using the single-linkage cluster algorithm (function clusterhr) or the LoCoH (e.g. function LoCoH.k).

The function plot.MCHu allows to graphically display the home-ranges.

MCHu.rast allows to compute a raster map of the home ranges.
MCHu2hrsize allows to compute the home range size for specified percentage levels for the home range (see help(plot.hrsize)).

spoldf2MCHu allows to convert a SpatialPolygonsDataFrame storing home ranges built by multiple convex hulls into an object of class "MCHu".

Usage

# S3 method for MCHu
print(x, ...)
# S3 method for MCHu
plot(x, percent="all", points=NULL, ...)
MCHu.rast(x, spdf, percent=100)
MCHu2hrsize(x, percent=seq(20,100, by=10), plotit=TRUE)
spoldf2MCHu(spdf, nam="a")

Value

The function MCHu.rast returns an object of class

SpatialPixelsDataFrame.

The function MCHu2hrsize returns an object of class

hrsize (see ?mcp.area).

Arguments

x

an object of class MCHu.

spdf

an object of class SpatialPixelsDataFrame.

points

an object of class SpatialPoints or SpatialPointsDataFrame with one column (a factor storing the identity of the animal for each relocation), containing the relocations of the animal(s).

percent

the percentage level of the home range. For the function plot.MCHu, this value could also be the character string "all", indicating that all the polygons are to be displayed.

plotit

a logical value indicating whether the results should be plotted.

nam

the name of the animal to be used in the object of class "MCHu".

...

additional arguments to be passed to the functions print and plot.

Author

Clement Calenge

Details

The class "MCHu" is basically a list of objects of class SpatialPolygonsDataFrame, with one data frame per animal.

See Also

clusthr and LoCoH for home range estimation methods returning this class of objects.

Examples

if (FALSE) {
data(puechabonsp)

## The relocations:
locs <- puechabonsp$relocs
locsdf <- as.data.frame(locs)
head(locsdf)

## Shows the relocations
plot(locs, col=as.numeric(locsdf[,1]))


## 12 points seems to be a good choice (rough asymptote for all animals)
## the k-LoCoH method:
nn <- LoCoH.k(locs[,1], k=12)

## Graphical display of the results
plot(nn, border=NA)

## Rasterize the home range on the elevation map:
image(puechabonsp$map)
(oo <- MCHu.rast(nn, puechabonsp$map))
image(oo)

}