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Spatial Analytics with ArcGIS

You're reading from   Spatial Analytics with ArcGIS Build powerful insights with spatial analytics

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781787122581
Length 290 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Eric Pimpler Eric Pimpler
Author Profile Icon Eric Pimpler
Eric Pimpler
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Table of Contents (11) Chapters Close

Preface 1. Introduction to Spatial Statistics in ArcGIS and R 2. Measuring Geographic Distributions with ArcGIS Tools FREE CHAPTER 3. Analyzing Patterns with ArcGIS Tools 4. Mapping Clusters with ArcGIS Tools 5. Modeling Spatial Relationships with ArcGIS Tools 6. Working with the Utilities Toolset 7. Introduction to the R Programming Language 8. Creating Custom ArcGIS Tools with ArcGIS Bridge and R 9. Application of Spatial Statistics to Crime Analysis 10. Application of Spatial Statistics to Real Estate Analysis

Introduction to Spatial Statistics in ArcGIS and R

Spatial statistics are a set of exploratory techniques for describing and modeling spatial distributions, patterns, processes, and relationships. Although spatial statistics are similar to traditional statistics, they also integrate spatial relationships into the calculations. In spatial statistics, proximity is important. Things that are closer together are more related.

ArcGIS includes the Spatial Statistics Tools toolbox available for all license levels of its desktop software. Included with this toolbox are a number of toolsets that help analyze spatial distributions, patterns, clustering, and relationships in GIS datasets. This book will cover each of the toolsets provided with the Spatial Statistics Tools toolbox in ArcGIS to provide a comprehensive survey of the spatial statistics tools available to ArcGIS users.

The R platform for data analysis is a programming language and software platform for statistical computing and graphics, and it is supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data analysts for developing statistical software and data analysis. In addition, R can be used for spatial statistical analysis and can also be integrated with ArcGIS through the R-ArcGIS Bridge.

This book also contains an introductory chapter for the R programming language as well as a chapter that covers the installation of the R-ArcGIS Bridge and the creation of custom ArcGIS script tools written with R.

In this chapter, we will cover the following topics:

  • Introduction to spatial statistics
  • An overview of the Spatial Statistics Tools toolbox in ArcGIS
  • An overview of the integration between R and ArcGIS
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