apcf

Adapted Pair Correlation Function


Keywords
gdal, geo, geos, point-pattern-analysis, r, r-package, spatial-statistics
License
CNRI-Python-GPL-Compatible

Documentation

apcf: Adapted Pair Correlation Function

Travis-CI Build Status AppVeyor Build Status Drone.io Status Package-License CRAN Dependencies DOI

The Adapted Pair Correlation Function transfers the concept of the Pair Correlation Function from point patterns to patterns of patches of finite size and irregular shape (eg. lakes within a country). The main tasks are (i) the construction of nullmodels by rondomizing the patches of the original pattern within the study area, (ii) the edge correction by determining the proportion of a buffer within the study area, and (iii) the calculation of the shortest distances between the patches.

This is a reimplementation of the Adapted Pair Correlation Function (Nuske et al. 2009) in C++ using the libraries GEOS and GDAL directly instead of through PostGIS.

Requirements

For Unix-alikes GDAL (>= 2.0.0) and GEOS (>= 3.4.0) are required.

On Ubuntu bionic (18.04) and beyond one can install the dependencies simply with sudo apt install libgdal-dev libgeos-dev. In earlier Ubuntu version either add ubuntugis-unstable to the sources.list and use above command or compile dependencies from source.

Installation

The stable version can be installed from CRAN

install.packages("apcf")

and the development is available from Github using the package remotes (formerly devtools)

if(!require("remotes")) install.packages("remotes")
remotes::install_github("rnuske/apcf")

Usage

# calculate distances between patches of original pattern and 3 nullmodels
# number of nullmodels should by at least 199 and better yet 999
ds <- pat2dists(area=system.file("shapes/sim_area.shp", package="apcf"),
                pattern=system.file("shapes/sim_pat_reg.shp", package="apcf"),
                max_dist=25, n_sim=3)

# derive PCF and envelope from distances
pcf <- dists2pcf(ds, r=0.2, r_max=25, stoyan=0.15, n_rank=1)

# plot PCF
plot(x=pcf, xlim=c(0, 20), ylim=c(0, 2.2))

Links

References

Nuske, R.S., Sprauer, S. and Saborowski J. (2009): Adapting the pair-correlation function for analysing the spatial distribution of canopy gaps. Forest Ecology and Management 259(1): 107–116. DOI: 10.1016/j.foreco.2009.09.050