Book Image

Spatial Analytics with ArcGIS

By : Eric Pimpler
Book Image

Spatial Analytics with ArcGIS

By: Eric Pimpler

Overview of this book

Spatial statistics has the potential to provide insight that is not otherwise available through traditional GIS tools. This book is designed to introduce you to the use of spatial statistics so you can solve complex geographic analysis. The book begins by introducing you to the many spatial statistics tools available in ArcGIS. You will learn how to analyze patterns, map clusters, and model spatial relationships with these tools. Further on, you will explore how to extend the spatial statistics tools currently available in ArcGIS, and use the R programming language to create custom tools in ArcGIS through the ArcGIS Bridge using real-world examples. At the end of the book, you will be presented with two exciting case studies where you will be able to practically apply all your learning to analyze and gain insights into real estate data.
Table of Contents (16 chapters)
Title Page
About the Author
About the Reviewer
Customer Feedback

Using Spatial Autocorrelation to analyze patterns

The Spatial Autocorrelation tool measures spatial autocorrelation by simultaneously measuring feature locations and attribute values. If features that are close together have similar values, then that is said to be clustering. However, if features that are close together have dissimilar values, then they are said to be dispersed. This tool outputs a Moran's I index value along with a z-score, and a p-value.

In this exercise, you'll use the Spatial Autocorrelation tool to analyze home sales by census tract.


Let's get prepared by performing the following steps for using the Spatial Autocorrelation tool to analyze patterns:

  1. Open ArcMap with the C:GeospatialTrainingSpatialStatsSeattleNeighborhoodBurglary.mxd file. You should see a polygon feature class called Seattle Neighborhood Burglary, as shown in the following screenshot:
  1. We'll first symbolize the data, so we have an idea about the contents of the data we'll be examining in this exercise...