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

Finding similar neighborhoods

In this section of the project, you will identify neighborhoods that are similar to the Stone Oak neighborhood where Lone Star Realty has it's current office location with respect to some basic real estate characteristics of the area. The results of this analysis will be used later in the chapter when we combine some additional analysis with the similarity search.

You will also generate a dataset that groups neighborhoods based on various real estate sales characteristics. Lone Star Realty will then use these groups to focus marketing efforts on those areas most common to its existing market area. Later in the chapter, we'll also identify neighborhoods where sales in the target market for Lone Star Realty have been strong over the past year and match those with the grouped neighborhoods defined by the grouping analysis.


The Similarity Search tool

The Similarity Search tool is used to identify candidate features that are most similar or most dissimilar to one or...