GIS Workshops - Spatial R



  Intro to GIS  |   Coordinates Systems  |   Exploratory Spatial Data Analysis  |   Points and Surfaces  |   GWR  |   Spatial Regression  |   Spatial R

There are a range of tools available for conducting Spatial Analysis. Recently, the R Programming language has seen a tremendous growth in functionality and documentation. This workshop is targeted towards individuals who are already doing spatial analysis, but want to know how to move their research into the R environment and to take advantage of some of R's constantly evolving suite of tools. Although we will consider some of the motivations for conducting the tests we use, this course is heavily focused on learning the software. Topics we will cover include: bringing spatial data into R, exploratory point pattern analysis, spatial weights matrices, global and local clustering statistics, and (briefly) spatial regression

Prerequisite: The workshop assumes a significant level of prior experience with GIS and limited familiarity with R. CSDE's introductory courses on R and at least a couple of the spatial analysis workshops are strongly recommended prior to taking this class.

Instructor

Chris Fowler
Raitt Hall 218M
csfowler@uw.edu
(206) 920-1686

Outline

  • Reading different data into R
  • Exploratory Point Pattern Analysis
    • Density
    • Nearest Neighbor Analysis
    • Ripley's K
  • Spatial Weights Matrices
    • Contiguity Matrices
    • Distance Matrices
  • Spatial Autocorrelation
    • Moran's I
    • LISA
  • Spatial Regression
    • Spatial Autocorrelation in OLS Residuals
    • Spatial Lag and Spatial Error Models

Materials


Further Reading

To register for the workshops, please complete the Registration Form.

3D Perspective view of crime density in Seattle




Example kernels for Kernel-Smoothed Density function