Marked Point Process: Using Correlation Functions to Explore a Spatial Data Set
✍ Scribed by Dr. Michel Goulard; L. Pagès; A. Cabanettes
- Publisher
- John Wiley and Sons
- Year
- 1995
- Tongue
- English
- Weight
- 788 KB
- Volume
- 37
- Category
- Article
- ISSN
- 0323-3847
No coin nor oath required. For personal study only.
✦ Synopsis
The relationship between the locations of the clumps of sprouts, some morphological characteristics of the clumps and the local soil environment in an old sweet chestnut coppice are studied. The theory of marked point process, which has not yet been used extensively in forestry studies, is shown to be adequate for the analysis of this type of spatial data. The marks correspond to morphological characteristics of the clumps: "diameter". "number of sprouts", "height at one year", and "height at three years". Several covariance functions are described which give a method for exploring the spatial relationships within the stand. Some of these functions are introduced for the first time in an actual statistical analysis.
By using these functions, it is shown that the clumps are regularly distributed. The variables "diameter" and "number of sprouts" are strongly spatially negatively correlated. whereas the heights are slightly or not correlated By categorising the individuals according to the mark values, it is shown that the small clumps tended to be aggregated in the gaps between medium and large clumps. Values of heights in the ties of the distribution are related as well as their spatial correlation to the local soil environment.
Les relations entre Ies positions de &pkes, leurs caractenstiqua morphologiques et Ie sol sont etudikes dans le 0s d'une plantation ancienne de chltaigners. La theorie des processus ponctuels marquts, qui a Cte peu utilike en foresterie. s'est montree adapt& pour I'analyse de a typc de donnks spatiales. La marque correspond ici a des caractenstiques morphologiques des CtpicS: "diametre", "nombre de rejets", "hauteur a un an" et "hauteur a trois ans". Plusieurs fonctions de covariance sont dtcritcs; ellcs ont fourni les moyens d'explorer I s relations spatiales du peuplement Certaincs de ces fonctions sont introduites pour la premiere fois dans une analyse statistique.
G r k a ces fonctions nous avons mis en evidence la distribution rCgulicre des CtpctS. Les variables "diamttre" et "nombre de rejets" montrent une forte correlation negative, les hauteurs ne p r k n t a n t peu ou pas de correlation spatiale. En classifiant les points suivant la valeur dcs marques, I'analyse montrc quc les pctitcs CcpCeS sont agn5gk.s dam l a vide laissls par l a moyennes et la grandes. Nom avons mis en evidence la liaison existant entre les valeun extemes des hauteurs, et leurs liaisons spatials, avtc le sol environnant. Unitt de recherches en tcophysiologie et horticulture ** Recherches Forestiires