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The goal of spatialising is to perform simulations of binary spatial raster data using the Ising model.


You can install the development version of spatialising from GitHub with:

# install.packages("devtools")


The spatialising package expects raster data with just two values, -1 and 1. Here, we will use the r_start.tif file built in the package.

r1 = rast(system.file("raster/r_start.tif", package = "spatialising"))

Most of the raster area is covered with the value of 1, and just about 5% of the area is covered with the value of -1. The main function in this package is kinetic_ising(). It accepts the input raster and at least two additional parameters: B – representing external pressure and J – representing the strength of the local autocorrelation tendency. The output is a raster modified based on the provided parameters.

r2 = kinetic_ising(r1, B = -0.3, J = 0.7)

The kinetic_ising() function also has a fourth argument called updates. By default, it equals to 1, returning just one raster as the output. However, when given a value larger than one, it returns many rasters. Each new raster is the next iteration of the Ising model of the previous one.

ri1 = kinetic_ising(r1, B = -0.3, J = 0.7, updates = 3)
plot(ri1, nr = 1)

Obtained results depend greatly on the set values of B and J. In the example above, values of B = -0.3 and J = 0.7 resulted in expansion of the yellow category (more -1 values).

On the other hand, values of B = 0.3 and J = 0.7 give a somewhat opposite result with less cell with the yellow category:

ri2 = kinetic_ising(r1, B = 0.3, J = 0.7, updates = 3)
plot(ri2, nr = 1)

Finally, in the last example, we set values of B = -0.3 and J = 0.4. Note that the result shows much more prominent data change, with a predominance of the yellow category only after a few updates.

ri3 = kinetic_ising(r1, B = -0.3, J = 0.4, updates = 3)
plot(ri3, nr = 1)


Read the related article:

  1. Stepinski, T. F. & Nowosad, J. (2023). The kinetic Ising model encapsulates essential dynamics of land pattern change, Royal Society Open Science,


Contributions to this package are welcome - let us know if you have any suggestions or spotted a bug. The preferred method of contribution is through a GitHub pull request. Feel also free to contact us by creating an issue.