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Spatial cluster detection using nearest neighbor distance

Bar-Hen A., Emily M., Picard N.. 2015. Spatial Statistics, 14 (Part C.) : p. 400-411.

DOI: 10.1016/j.spasta.2015.07.006

Motivated by the analysis of the impact of ecological processes on spatial distribution of tree species, we introduce in this paper a novel approach to detect spatial cluster of points. Our procedure is based on an iterative transformation of the distance between points into a measure of closeness. Our measure has the advantage of being independent of an arbitrary cluster shape and allowing adjustment for covariates. The comparison of the observed measure of closeness to a reference point process leads to a hierarchical clustering of spatial points. The selection of the optimal number of clusters is performed using the Gap statistic. Our procedure is illustrated on a spatial distribution of the Dicorynia guianensis species in the French Guiana terra firme rainforest.

Mots-clés : forêt tropicale humide; dynamique des populations; distribution géographique; modèle de simulation; méthode statistique; régime sylvicole; classification; espacement; Écologie forestière; peuplement forestier; guyane française; france; dicorynia guianensis

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