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Second-Order Neighborhood Analysis of Mapped Point Patterns

  • Arthur Getis
  • Janet Franklin
Chapter
Part of the Advances in Spatial Science book series (ADVSPATIAL)

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.

References

  1. Bartlett MS (1950) Periodogram analysis and continuous spectra. Biometrika 37:1–16Google Scholar
  2. Diggle PJ (1983) Statistical analysis of spatial point patterns. Academic, LondonGoogle Scholar
  3. Franklin J, Michaelsen J, Strahler AH (1985) Spatial analysis of density dependent pattern in coniferous forest stands. Vegetatio 64:29–36CrossRefGoogle Scholar
  4. Getis A (1984) Interaction modeling using second-order analysis. Environ Plan A 16:173–183CrossRefGoogle Scholar
  5. Grieg-Smith P (1983) Quantitative plant ecology, 3rd edn. Blackwell, OxfordGoogle Scholar
  6. Moellering H, Tobler WR (1972) Geographical variances. Geogr Anal 4:34–50CrossRefGoogle Scholar
  7. Pacala S, Silander J Jr (1985) Neighborhood models of plant population dynamics. I. Single-species models of annuals. Am Nat 125:385–411Google Scholar
  8. Pielou E (1977) Mathematical ecology. Wiley, New YorkGoogle Scholar
  9. Rayner JN (1971) An introduction to spectral analysis. Pion, LondonGoogle Scholar
  10. Ripley BD (1977) Modelling spatial patterns (with discussion). J R Stat Soc B 39:172–212Google Scholar
  11. Ripley BD (1981) Spatial statistics. Wiley, New YorkCrossRefGoogle Scholar
  12. Robinson A, Sale R, Morrison J, Muehrcke P (1984) Elements of cartography, 5th edn. Wiley, New YorkGoogle Scholar
  13. Weiner J (1984) Neighbourhood in interference amongst Pinus rigida individuals. J Ecol 72: 183–195CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Department of GeographySan Diego State UniversitySan DiegoUSA
  2. 2.School of Geographical Sciences and Urban Planning, and School of Life SciencesArizona State UniversityArizonaUSA

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