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osc: Orthodromic Spatial Clustering

Allows distance based spatial clustering of georeferenced data by implementing the City Clustering Algorithm - CCA. Multiple versions allow clustering for matrix, raster and single coordinates on a plain (euclidean distance) or on a sphere (great-circle or orthodromic distance).

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Version

Install

install.packages('osc')

Monthly Downloads

142

Version

1.0.5

License

GPL

Last Published

December 19th, 2019

Functions in osc (1.0.5)

coordinate.list

List of coordinates for clustering
population

Example population data for the city clustering algorithm
exampledata

Example data for the clustering algorithm.
osc.buffer

Simple Buffer algorithm
assign.data

Assign data to clusters
cca

City Clustering Algorithm (CCA)
landcover

Fictional landcover data to demonstrate the cca for Raster-Data