Spatial cluster detection using nearest neighbor distance
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.
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Bibliographic Details
| Main Authors: |
Bar-Hen, Avner,
Emily, Mathieu,
Picard, Nicolas |
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| Format: | article
biblioteca
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| Language: | eng |
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| Subjects: | K10 - Production forestière,
U10 - Informatique, mathématiques et statistiques,
F40 - Écologie végétale,
forêt tropicale humide,
dynamique des populations,
distribution géographique,
modèle de simulation,
méthode statistique,
régime sylvicole,
classification,
espacement,
écologie forestière,
peuplement forestier,
http://aims.fao.org/aos/agrovoc/c_7976,
http://aims.fao.org/aos/agrovoc/c_6111,
http://aims.fao.org/aos/agrovoc/c_5083,
http://aims.fao.org/aos/agrovoc/c_24242,
http://aims.fao.org/aos/agrovoc/c_7377,
http://aims.fao.org/aos/agrovoc/c_7070,
http://aims.fao.org/aos/agrovoc/c_1653,
http://aims.fao.org/aos/agrovoc/c_7272,
http://aims.fao.org/aos/agrovoc/c_3044,
http://aims.fao.org/aos/agrovoc/c_28080,
http://aims.fao.org/aos/agrovoc/c_3093,
http://aims.fao.org/aos/agrovoc/c_3081, |
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| Online Access: | http://agritrop.cirad.fr/577151/
http://agritrop.cirad.fr/577151/7/577151_version_editee.pdf
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