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  • Book Overview & Buying Spatial Analytics with ArcGIS
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Spatial Analytics with ArcGIS

Spatial Analytics with ArcGIS

By : Eric Pimpler
4 (1)
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Spatial Analytics with ArcGIS

Spatial Analytics with ArcGIS

4 (1)
By: Eric Pimpler
Buy this Book

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

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.

Preparation

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...
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Spatial Analytics with ArcGIS
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