Second-order neighborhood analysis of mapped point patterns

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.