Point pattern analysis : A tutorial
Point pattern analysis focuses on the analysis and visualization of the spatial distribution of points. With the increasing availability of geolocation data, more and more individual-level point data are generated. We illustrate the analysis of point patterns through a series of real-world examples that make use of various R packages and functions.
The R-script and the data to replicate the examples (accessible via a series of zip-files, part1.zip to part5.zip) are available on my github.
Contents of tutorial:
Introduction
package SPATSTAT
Point pattern analysis in R :
Example 1 : Drumlins data
Example 2 : Crime data
Example 3 : London transport points
Example 4 : POS data Belgium
Example 5 : Kernel density with kde2d function
Example 6 : Clipping a raster (1)
Example 7 : Clipping a raster (2)
Example 8 : Smooth.ppp
Example 9 : Kernel density estimation with package spatstat
Example 10 : Kernel density estimation with package sm
Example 11 : Density of retail outlets in Belgium
Example 12 : Data from Openstreetmap (data not available on my github)
Example 13 : Point analysis Wikileaks Iraq data
Example 14 : Heatmap traffic signals Toronto
Example 15 : stat_summary2d plot
Example 16 : Convert lat-lon coordinates / UTM coordinates
Example 17 : Stat density plots of Baltimore crime data
Example 18 : Point pattern analysis of 311 requests NYC
Example 19 : Point patterns with package "squash"
Example 20 : Dot density maps in R
Example 21 : Heatmap raster in QGis 2.4
Example 22 : Gathering tweets and plot lon/lat coordinates (data not available on my github)
Example 23 : Concentric circles as points in ggplot2 / ggmap
Example 24 : Import a csv-file in Tilemill and edit the data (data not available on my github)
Example 25 : Combine data and spatial locations
Example 26 : Spatiotemporal point observations