comat

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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).

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")

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

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

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.

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")