Overlap indices can be useful for determining the spatial interactions between animals using relocations of animals occupying similar areas. There are various overlap indices available and a good reference is Fieberg and Kochanny (2005). The overlap methods presented have code and more detailed descriptions in the adehabitatHR package for R (Calenge 2011). Methods of home range overlap simply require coordinate data after estimating home range. Note that example below is not the same dataset supplied for this exercise.
#First we can load some data and create some generic utilization distributions before estimating overlap:
library(adehabitatHR)
#Creates a Spatial Points Data Frame for 2 animals by ID
twocats <-read.csv("C:\\Walter\\WalterSpatialEcologyLab\\SpatialEcologyCourse\\
Chapter5\\Overlap\\AllHRlocs.csv", header=T)
data.xy = twocats[c("x","y")]
#Creates class Spatial Points for all locations
xysp <- SpatialPoints(data.xy)
proj4string(xysp) <- CRS("+proj=utm +zone=17N +ellps=WGS84")
#Creates a Spatial Data Frame from all locations
sppt<-data.frame(xysp)
#Creates a spatial data frame of ID
idsp<-data.frame(twocats[1])
#Merges ID data frame with GPS locations data frame
#Data frame is called "idsp" comparable to the "relocs" from puechabon dataset
coordinates(idsp)<-sppt
#First we need to create utilization distributions for each panther
ud <- kernelUD(idsp[,1])
OR
kernelUD(idsp[,1], h = "href", grid = 200, same4all = TRUE, hlim = c(0.1, 1.5), kern = c("bivnorm"), extent = 0.5)
#output of UDs for each panther
image(ud)
NOTE: kerneloverlap will just estimate overlap indices for only the locations
