Creates Co-Occurrence Matrices of Spatial Data.

comat

The goal of comat is to create co-occurrence matrices based on spatial data, including a weighted co-occurrence matrix (wecoma) and an integrated co-occurrence matrix (incoma).

Installation

You can install the released version of comat from CRAN with:

install.packages("comat")

You can install the development version from GitHub with:

# install.packages("remotes")
remotes::install_github("Nowosad/comat")

Example

This is a basic example which shows you how to create a weighted co-occurrence matrix (wecoma) based on two simple rasters (for simplicity presented as matrices). The first one raster_x represents some categories, and the second one raster_w represents weights.

library(comat)
library(raster)
#> Loading required package: sp
data(raster_x, package = "comat")
data(raster_w, package = "comat")
raster_x
#>      [,1] [,2] [,3]
#> [1,]    1    1    3
#> [2,]    1    3    3
#> [3,]    2    2    3
raster_w
#>      [,1] [,2] [,3]
#> [1,]    2    2    9
#> [2,]    6    4    9
#> [3,]    4    8    9

The get_wecoma() function can be next used to create a weighted co-occurrence matrix.

get_wecoma(
  raster_x,
  raster_w,
  neighbourhood = 4
)
#>      1    2    3
#> 1 12.0  5.0 13.5
#> 2  5.0 12.0 14.5
#> 3 13.5 14.5 49.0

This function allows for some parametrization using additional arguments, e.g.:

get_wecoma(
  raster_x,
  raster_w,
  neighbourhood = 4,
  fun = "focal",
  na_action = "keep"
)
#>    1  2  3
#> 1 12  6 10
#> 2  4 12 16
#> 3 17 13 49

Documentation

For more examples see the package’s vignettes:

1. A co-occurrence matrix (coma) representation
2. A weighted co-occurrence matrix (wecoma) representation
3. An integrated co-occurrence matrix (incoma) representation

Contribution

Contributions to this package are welcome. The preferred method of contribution is through a GitHub pull request. Feel free to contact me by creating an issue.

Citation

To cite the comat package in publications, please use this paper:

Nowosad J, Stepinski TF (2021) Pattern-based identification and mapping of landscape types using multi-thematic data, International Journal of Geographical Information Science, DOI: 10.1080/13658816.2021.1893324

LaTeX/BibTeX version can be obtained with:

library(comat)
citation("comat")