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3 - Analyzing Geographic Distributions and Point Patterns

Published online by Cambridge University Press:  20 May 2020

George Grekousis
Affiliation:
Sun Yat-Sen University (SYSU), China
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Summary

This chapter deals with

  • Calculating basic statistics for analyzing geographic distributions including mean center, median center, central feature, standard distance and standard deviational ellipse (centrographics)

  • Explaining how these metrics can be used to describe spatial arrangements of different sets of point patterns

  • Defining locational and spatial outliers

  • Introducing the notions of complete spatial randomness, first-order effects and second-order effects

  • Analyzing point patterns through average nearest neighbor analysis

  • Ripley’s K function

  • Kernel density estimation

  • Randomness and the meaning of spatial process in creating point patterns

    After a thorough study of the theory and lab sections, you will be able to

  • Use spatial statistics to describe the distribution of point patterns

  • Identify locational and spatial outliers

  • Use statistical tools and tests to identify if a spatial point pattern is random, clustered or dispersed

  • Use Ripley’s K and L functions to define the appropriate scale of analysis

  • Use kernel density functions to produce smooth surfaces of points’ intensity over space

  • Apply centrographics, conduct point pattern analysis, apply jernel density estimator and trace locational outliers through ArcGIS

Type
Chapter
Information
Spatial Analysis Methods and Practice
Describe – Explore – Explain through GIS
, pp. 147 - 206
Publisher: Cambridge University Press
Print publication year: 2020

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