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Spatial Analytics with ArcGIS: Build powerful insights with spatial analytics
Paperback
ISBN13: 9781787122581
Publisher: Packt Pub
Published: Apr 26 2017
Pages: 290
Weight: 1.11
Height: 0.61 Width: 7.50 Depth: 9.25
Language: English
Pattern Analysis and cluster mapping made easy
Key Features:
- Analyze patterns, clusters, and spatial relationships using ArcGIS tools
- Get up to speed in R programming to create custom tools for analysis
- Sift through tons of crime and real estate data and analyze it using the tools built in the book
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.
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
Who this book is for:
This book is for ArcGIS developers who want to perform complex geographic analysis through the use of spatial statistics tools including ArcGIS and R. No knowledge of R is assumed.
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