In dabrowskia/dspace: Dividing Space - Data Driven Segementation of Spatial Data

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

dspace

Overview

The goal of dspace is to enable researchers to delineate real estate submarkets based on the information within the data. Current methods usually depend on pre-existing, subjective divisions, eg. administrative boundaries or school districts. The method implemented here uses graph analysis for finding communities in network to cluster together point or polygon objects based on their similarity.

Installation

You can install the development version from GitHub with:

# install.packages("remotes")
remotes::install_github("dabrowskia/dspace")

Development version

To get a bug fix or to use a feature from the development version, you can install the development version of dspace from GitHub.

# install.packages("devtools")
devtools::install_github("dabrowskia/dspace")

Usage

library(dspace)
data("socioGrid")
modularity <- find_no_clusters(socioGrid, disjoint = TRUE, n.neigh = 6)
plot_modularity(modularity)
socioGrid$class <- regionalize(socioGrid, k = 7,
   disjoint = TRUE, plot = TRUE)

data("realEstate")
realEstate$class <- regionalize(realEstate, k = 5, accuracy = FALSE)