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.
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Getis, A., Franklin, J. (2010). Second-Order Neighborhood Analysis of Mapped Point Patterns. In: Anselin, L., Rey, S. (eds) Perspectives on Spatial Data Analysis. Advances in Spatial Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01976-0_7
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DOI: https://doi.org/10.1007/978-3-642-01976-0_7
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Online ISBN: 978-3-642-01976-0
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