somspace: Spatial Analysis with Self-Organizing Maps

Application of the Self-Organizing Maps technique for spatial classification of time series. The package uses spatial data, point or gridded, to create clusters with similar characteristics. The clusters can be further refined to a smaller number of regions by hierarchical clustering and their spatial dependencies can be presented as complex networks. Thus, meaningful maps can be created, representing the regional heterogeneity of a single variable. More information and an example of implementation can be found in Markonis and Strnad (2020, <doi:10.1177/0959683620913924>).

Version: 1.2.4
Depends: R (≥ 3.5.0), ggplot2, data.table, kohonen
Imports: maps, reshape2
Suggests: knitr, rmarkdown, testthat
Published: 2023-04-28
DOI: 10.32614/CRAN.package.somspace
Author: Yannis Markonis [aut, cre], Filip Strnad [aut], Simon Michael Papalexiou [aut], Mijael Rodrigo Vargas Godoy [ctb]
Maintainer: Yannis Markonis <imarkonis at>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: somspace results


Reference manual: somspace.pdf
Vignettes: somspace: Spatial classification with Self-Organizing Maps


Package source: somspace_1.2.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): somspace_1.2.4.tgz, r-oldrel (arm64): somspace_1.2.4.tgz, r-release (x86_64): somspace_1.2.4.tgz, r-oldrel (x86_64): somspace_1.2.4.tgz
Old sources: somspace archive


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