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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 FREE CHAPTER 2. Measuring Geographic Distributions with ArcGIS Tools 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

Using the Optimized Hot Spot Analysis tool in real estate sales


Many analysts have difficulty in defining the neighborhood for their analysis. The neighborhood you define should match the question you are asking. For example, a study of obesity in California counties would need a large neighborhood due to the size of counties. However, a study of real estate sales for a metro area would need a much smaller neighborhood. If you are unsure of the distance to use for the neighborhood calculation, the Optimized Hot Spot Analysis tool will calculate the optimized neighborhood along with simplifying and optimizing some of the other input parameters. For example, it tosses out outliers. However, keep in mind that it automatically uses FIXED_DISTANCE as its conceptualization of spatial relationship, and this may not be appropriate in your particular study. In this exercise, you'll learn how to use the Optimized Hot Spot Analysis tool to determine hot and cold spots of residential real estate sales...

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