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:
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.
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:
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: