Spatial KWD for Large Spatial Maps

Contains efficient implementations of Discrete Optimal Transport algorithms for the computation of Kantorovich-Wasserstein distances between pairs of large spatial maps (Bassetti, Gualandi, Veneroni (2020), ). All the algorithms are based on an ad-hoc implementation of the Network Simplex algorithm. The package has four main helper functions: compareOneToOne() (to compare two spatial maps), compareOneToMany() (to compare a reference map with a list of other maps), compareAll() (to compute a matrix of distances between a list of maps), and focusArea() (to compute the KWD distance within a focus area). In non-convex maps, the helper functions first build the convex-hull of the input bins and pad the weights with zeros.


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install.packages("SpatialKWD")

0.4.0 by Stefano Gualandi, 4 months ago


Browse source code at https://github.com/cran/SpatialKWD


Authors: Stefano Gualandi [aut, cre]


Documentation:   PDF Manual  


EUPL (>= 1.2) license


Imports methods, Rcpp

Linking to Rcpp

System requirements: C++11


See at CRAN