Spatial Analytics with ArcGIS

Pattern Analysis and cluster mapping made easy

Spatial Analytics with ArcGIS

Eric Pimpler

Pattern Analysis and cluster mapping made easy
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Book Details

ISBN 139781787122581
Paperback290 pages

Book Description

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

Chapter 1: Introduction to Spatial Statistics in ArcGIS and R
Introduction to spatial statistics
An overview of the Spatial Statistics Tools toolbox in ArcGIS
Integrating R with ArcGIS
Summary
Chapter 2: Measuring Geographic Distributions with ArcGIS Tools
Measuring geographic centrality
The Standard Distance and Directional Distribution tools
Summary
Chapter 3: Analyzing Patterns with ArcGIS Tools
The Analyzing Patterns toolset
Using the Average Nearest Neighbor tool
Using Spatial Autocorrelation to analyze patterns
Using the Multi-Distance Spatial Cluster Analysis tool to determine clustering or dispersion
Summary
Chapter 4: Mapping Clusters with ArcGIS Tools
Using the Similarity Search tool
Using the Grouping Analysis tool
Analysing real estate sales with the Hot Spot Analysis tool
Using the Optimized Hot Spot Analysis tool in real estate sales
Creating Hot Spot maps from point data using the Optimized Hot Spot Analysis tool
Finding outliers in real estate sales activity using the Cluster and Outlier Analysis tool
Summary
Chapter 5: Modeling Spatial Relationships with ArcGIS Tools
The basics of Regression Analysis
Linear regression with the Ordinary Least Squares (OLS) tool
Using the Exploratory Regression tool
Using the Geographically Weighted Regression tool
Summary
Chapter 6: Working with the Utilities Toolset
The Calculate Distance Band from Neighbor Count tool
The Collect Events tool
The Export Feature Attribute to ASCII tool
Summary
Chapter 7: Introduction to the R Programming Language
Installing R and the R interface
Variables and assignment
R data types
Additional R study options
Summary
Chapter 8: Creating Custom ArcGIS Tools with ArcGIS Bridge and R
Installing the R-ArcGIS Bridge package
Building custom ArcGIS tools with R
Summary
Chapter 9: Application of Spatial Statistics to Crime Analysis
Obtaining the crime dataset
Using the Mapping Clusters tool in vehicle theft data
Summary
Chapter 10: Application of Spatial Statistics to Real Estate Analysis
Obtaining the Zillow real estate datasets
Data preparation
Finding similar neighborhoods
Finding areas of high real estate sales activity
Recommendations for the client
Summary

What You Will Learn

  • Get to know how to measure geographic distributions
  • Perform clustering analysis including hot spot and outlier analysis
  • Conduct data conversion tasks using the Utilities toolset
  • Understand how to use the tools provided by the Mapping Clusters toolset in the Spatial Statistics Toolbox
  • Get to grips with the basics of R for performing spatial statistical programming
  • Create custom ArcGIS tools with R and ArcGIS Bridge
  • Understand the application of Spatial Statistics tools and the R programming language through case studies

Authors

Table of Contents

Chapter 1: Introduction to Spatial Statistics in ArcGIS and R
Introduction to spatial statistics
An overview of the Spatial Statistics Tools toolbox in ArcGIS
Integrating R with ArcGIS
Summary
Chapter 2: Measuring Geographic Distributions with ArcGIS Tools
Measuring geographic centrality
The Standard Distance and Directional Distribution tools
Summary
Chapter 3: Analyzing Patterns with ArcGIS Tools
The Analyzing Patterns toolset
Using the Average Nearest Neighbor tool
Using Spatial Autocorrelation to analyze patterns
Using the Multi-Distance Spatial Cluster Analysis tool to determine clustering or dispersion
Summary
Chapter 4: Mapping Clusters with ArcGIS Tools
Using the Similarity Search tool
Using the Grouping Analysis tool
Analysing real estate sales with the Hot Spot Analysis tool
Using the Optimized Hot Spot Analysis tool in real estate sales
Creating Hot Spot maps from point data using the Optimized Hot Spot Analysis tool
Finding outliers in real estate sales activity using the Cluster and Outlier Analysis tool
Summary
Chapter 5: Modeling Spatial Relationships with ArcGIS Tools
The basics of Regression Analysis
Linear regression with the Ordinary Least Squares (OLS) tool
Using the Exploratory Regression tool
Using the Geographically Weighted Regression tool
Summary
Chapter 6: Working with the Utilities Toolset
The Calculate Distance Band from Neighbor Count tool
The Collect Events tool
The Export Feature Attribute to ASCII tool
Summary
Chapter 7: Introduction to the R Programming Language
Installing R and the R interface
Variables and assignment
R data types
Additional R study options
Summary
Chapter 8: Creating Custom ArcGIS Tools with ArcGIS Bridge and R
Installing the R-ArcGIS Bridge package
Building custom ArcGIS tools with R
Summary
Chapter 9: Application of Spatial Statistics to Crime Analysis
Obtaining the crime dataset
Using the Mapping Clusters tool in vehicle theft data
Summary
Chapter 10: Application of Spatial Statistics to Real Estate Analysis
Obtaining the Zillow real estate datasets
Data preparation
Finding similar neighborhoods
Finding areas of high real estate sales activity
Recommendations for the client
Summary

Book Details

ISBN 139781787122581
Paperback290 pages
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