Point Pattern Analysis. Methods for analyzing completely censused population data F Entire extent of study area or F Each unit of an array of contiguous.

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Presentation transcript:

Point Pattern Analysis

Methods for analyzing completely censused population data F Entire extent of study area or F Each unit of an array of contiguous sample units (e.g. quadrats) F Global vs. Local F Entire extent of study area or F Each unit of an array of contiguous sample units (e.g. quadrats) F Global vs. Local

Types of Point data F Univariate, Bivariate, Multivariate F 1, 2, and 3 Dimensions (x,y,z) F Univariate, Bivariate, Multivariate F 1, 2, and 3 Dimensions (x,y,z)

Point Pattern Analysis F Pattern may change with scale! F Test statistic calculated from data vs. expected value of statistic under CSR (complete spatial randomness) F Pattern may change with scale! F Test statistic calculated from data vs. expected value of statistic under CSR (complete spatial randomness)

Types of Point Patterns F Random (CSR) F Overdispersed (spaced or regular) F Underdispersed (clumped or aggregated) F Random (CSR) F Overdispersed (spaced or regular) F Underdispersed (clumped or aggregated)

Methods F Distance to neighbor F sample F Refined Nearest Neighbor F randomization F Second-order point pattern analysis F Distance to neighbor F sample F Refined Nearest Neighbor F randomization F Second-order point pattern analysis

Second-order Point Pattern Analysis: Ripley’s K “Used to analyse the mapped positions of events in the plane… and assume a complete census…” “Used to analyse the mapped positions of events in the plane… and assume a complete census…”