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Second-Order Neighborhood Analysis of Mapped Point Patterns

In: Perspectives on Spatial Data Analysis

Author

Listed:
  • Arthur Getis

    (San Diego State University)

  • Janet Franklin

    (Arizona State University)

Abstract

A technique based on second-order methods, called second-order neighborhood analysis, is used to quantify clustering at various spatial scales. The theoretical model represents the degree of clustering in a Poisson process from the perspective of each individual point. The method is applied to point location data for a sample of ponderosa pine (Pinus ponderosa) trees, and shows that heterogeneity within the forest is clearly a function of the scale of analysis.

Suggested Citation

  • Arthur Getis & Janet Franklin, 2010. "Second-Order Neighborhood Analysis of Mapped Point Patterns," Advances in Spatial Science, in: Luc Anselin & Sergio J. Rey (ed.), Perspectives on Spatial Data Analysis, chapter 0, pages 93-100, Springer.
    • Handle: RePEc:spr:adspcp:978-3-642-01976-0_7
    DOI: 10.1007/978-3-642-01976-0_7
    as

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    Citations

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    Cited by:

    1. Jonatan A. González & Francisco J. Rodríguez-Cortés & Elvira Romano & Jorge Mateu, 2021. "Classification of Events Using Local Pair Correlation Functions for Spatial Point Patterns," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(4), pages 538-559, December.
    2. Matthias Eckardt & Jorge Mateu, 2021. "Second-order and local characteristics of network intensity functions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 318-340, June.

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