spatmap

Author: Grant Morrison([email protected])

spatmap is an R package for the visualization of local spatial statistics. The mapping functions support a variety of local spatial statistics with cluster maps and significance maps. These include Local Moran, Local Geary, Local Join Count, Local G, and Local G*. There are multivariate options for the Local Geary and Local Join Count statistics. The statistical computation is done by the package rgeoda by Xun Li. The visualization of these statistics is built off of tmap to give a range range of formatting options and interactivity.

Installation

Both spatmap and rgeoda are not available through CRAN, so you must install them remotely. We use install_github from remotes to install both of these packages.

remotes::install_github("lixun910/rgeoda")
remotes::install_github("morrisonge/spatmap")

Goals and Objectives

• Visualization of Local Moran Cluster and Significance Maps

• Visualization of Univariate and Multivariate Local Geary Cluster and Significance Maps

• Visualization of Local G and G* Cluster and Significance Maps

• Visualization of Univariate and Multivariate Local Join Count Cluster and Significance Maps

Data Description

The data used in the vignette for this package is from the GeoDa website and will be loaded from the geodaData package by Angela Li. The dataset is originall from a classic social science study in the 1800's, and is now used as apart of the GeoDa workbook tutorials. To get access to this data, we will need to install geodaData from github.

remotes::install_github("spatialanalysis/geodaData")

The dataset is from a classic social science study by Andre-Michel Guerry on crime, suicide , and other “moral” statistics. It is available on the GeoDa website. The spatial resolution is the prefecture-level, which is similar to the county-level. Each polygon has measures for different “moral” statistics of the area. There is some degree of temporal resolution with averages of the variables pertaining to different sets of years. These years range from 1815 to 1834. There are 23 variables in the dataset, and 85 observations. I will only be using a few of these variables for the project vignette.

Variables included:

• Donatns: Donations to the poor

• Infants: Population per illegitimate birth

• doncat: Categorical Variable based on Donatns. The top quintile is assigned 1 and the rest 0

• doncat: Categorical Variable based on Infants. The top quintile is assigned 1 and the rest 0

Local Statistics Maps

Local Moran Cluster Map

Local Geary Cluster Map

Multivariate Local Geary Cluster Map

Local Join Count Cluster Map

Multivariate Local Join Count Cluster Map

Local G Cluster Map

Significance Map

Tutorials

spatmap

Future Work

Add package to CRAN or add the mapping functions to rgeoda