Spatial Analytics with ArcGIS

Pattern Analysis and cluster mapping made easyAbout This BookAnalyze patterns, clusters, and spatial relationships using ArcGIS toolsGet up to speed in R programming to create custom tools for analysisSift through tons of crime and real estate data and analyze it using the tools built in the bookWho This Book Is ForThis 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.What You Will LearnGet to know how to measure geographic distributionsPerform clustering analysis including hot spot and outlier analysisConduct data conversion tasks using the Utilities toolsetUnderstand how to use the tools provided by the Mapping Clusters toolset in the Spatial Statistics ToolboxGet to grips with the basics of R for performing spatial statistical programmingCreate custom ArcGIS tools with R and ArcGIS BridgeUnderstand the application of Spatial Statistics tools and the R programming language through case studiesIn DetailSpatial 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.Style and approachFilled with live examples that you can code along with, this book will show you different methods and techniques to effectively analyze spatial data with ArcGIS and the R language. The exciting case studies at the end will help you immediately put your learning to practice.