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, Ensuite pour chaque arbre t on met à jour les caractéristiques de ses voisins

. Ensuite, récupère les identifiants des voisins de l'arbre t à l'année n. Ces identifiants nous

, Update new trees neighbourhoods: same tree ids than next year but trees of newStand for (Iterator j = refStand.getTrees ().iterator (); j.hasNext ();) { Opi2Tree t = (Opi2Tree) j

, // SAME neighbour distances map : CAUTION: SAME REFERENCE, // TO BE CHECKED WHEN MORTALITY OR REGENERATION WILL BE ADDED newTree.setNeighbourDistances (t.getNeighbourDistances (

, Opi2Tree newN = (Opi2Tree) newStand.getTree (nId)

, newOakNeighbours.add (newN

, } newTree.setOakNeighbours (newOakNeighbours)

, Modification de la liste des voisins lors d'une éclaircie Après une éclaircie, on fait intervenir la méthode processPostThinning de la classe de la classe Opi2Model, Les arbres dans oakpine2 ont un champ effectif. Dans les modèles, 2008.

, Si un arbre a été enlevé, son identifiant n'est plus dans le peuplement, la distance ne figure plus dans la table des distances : CemOA : archive ouverte d'Irstea / Cemagref

, For each tree in the thinned stand, update its oak / pine neighbour collections: // remove the ids of the cut neighbours for (Iterator i = std.getTrees ().iterator (); i.hasNext ();) { Opi2Tree t = (Opi2Tree) i

, for (Iterator j = oaks.iterator (); j.hasNext ();) { Opi2Tree n = (Opi2Tree) j

, for (Iterator j = pines.iterator (); j.hasNext ();) { Opi2Tree n = (Opi2Tree) j

}. ,

. Map<integer, Double> map = t.getNeighbourDistances (

. Map&lt;integer, Double> newMap = new HashMap<Integer,Double> (

, { if (std.getIds ().contains (nId)) { double distance = map

, newMap

. }-}-t.setneighbourdistances,

, } Conclusion et perspectives Dans ce document nous avons présenté comment nous avons implémenté un modèle arbre avec distribution de voisinage (Oakpine2) dans la plate-forme Capsis. Nous avons précisé les données d'entrée nécessaires au fonctionnement du module

, Au cours de l'implémentation, nous avons réalisé à plusieurs reprises des vérifications

, Nous avons en particulier vérifié que les distributions étaient bien respectées grâce à l'extracteur de données qui permet de visualiser les résultats des tirages sous la forme d'histogrammes. Nous avons également réalisé des comparaisons qualitatives entre les

, Nous avons été amenés à faire certains choix au cours de l'implémentation

F. D. Coligny, P. Ancelin, G. Cornu, B. Courbaud, P. Dreyfus et al., CAPSIS : Computer-Aided Projection for Strategies In Silviculture : Advantages of a shared forest-modelling platform. International Workshop of IUFRO working party 4.01 "Reality, models and parameter estimation, pp.319-323, 2002.
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T. Perot and F. Goreaud, Oakpine2: A tree model using neighbourhood distributions to describe mixed forest growth. 10ème réunion Capsis, 2008.