In qspatialR/qspatial: Areal and Point Pattern Data Visualization and Analysis

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qspatial

qspatial is a spatial statistics package for R made with an user-friendly approach to allow users who are new to R or spatial statistics to visualize and analyze spatial data. The package utilizes spatstat and spdep functions to do the spatial analysis and ggplot2 to create all the resulting maps and plots.

The current version of the package has functions for point pattern and areal data. The package's functions uses what is considered a common methodology found in the literature, as an example, for areal data the functions automatically creates the neighborhood and the weight's matrix.

Installation

You can install the released version of qspatial from github with:

# install.packages("devtools")
devtools::install_github("qspatialR/qspatial")

Examples

Areal Data

The main function for areal data is the lmoranmap function. It produces four maps: one with the counts, one with the value of the Local Moran's I result for each area unit, one showing the neighborhood structure used and one showing which area units are spatially dependant under a certain significance level and also showing the Moran categories for these areas.

The package contains data for Dengue fever counts in the state of Rio de Janeiro for the period between 2009 and 2013. A shapefile for Rio de Janeiro is also included so the examples on the function can be tested.

library(qspatial)
library(maptools)
dengue.data = dengue
rio = rioshapefile

dengue2010 = lmoranmap(shapefile = rio, adata = dengue.data$`2010`)

dengue.data = dengue
rio = rioshapefile

dengue2010 = lmoranmap(shapefile = rio, adata = dengue.data$`2010`)

plot(dengue2010)

It's also possible to create the neighbourhoods using the knearneigh function from spdep, in this case the k areas with the nearest centroids will be considered as neighbours.

library(qspatial)
dengue.data = dengue
rio = rioshapefile

dengue2010 = lmoranmap(shapefile = rio, adata = dengue.data$`2010`, knearest = 5)

dengue.data = dengue
rio = rioshapefile

dengue2010 = lmoranmap(shapefile = rio, adata = dengue.data$`2010`, knearest = 5)

plot(dengue2010)

The areamap function works in a similar way to the sp's spplot function, it receives a shapefile and a vector of data and generates the map using ggplot2.

dengue.data = dengue
rio = rioshapefile

dengue2010map = areamap(shapefile = rio, adata = dengue.data$`2010`,
maptitle = "Dengue counts for Rio de Janeiro in 2010",
guidetitle = "Frequency")

dengue2010map = areamap(shapefile = rio, adata = dengue.data$`2010`,
maptitle = "Dengue counts for Rio de Janeiro in 2010",
guidetitle = "Frequency")

plot(dengue2010map)

Point Pattern Data

The main function for point pattern data is qmpattern. It produces four plots: A map with the ocurrences, a map for the Intensity and two plots of the summary functions. By default the function uses the G and F functions which are computationally cheaper, but the K and J functions are also available.

The included data is about traffic accidents in Recife, Brazil. The locations of the accidents are registered by latitude and longitude coordinates, a shapefile of the city is also included in the package.

accidents.data = acidentes
recife = recife

accidents.map = qmpattern(shapefile = recife, longitude = accidents.data$longitude, accidents.data$latitude, fun = c("G", "F"), sigma = 0.01, nsim = 5)

accidents.data = acidentes
recife = recife

accidents.map = qmpattern(shapefile = recife,
longitude = accidents.data$longitude, accidents.data$latitude,
fun = c("G", "F"), sigma = 0.01, nsim = 5)