The spatial structure of a forest stand is an important signature of forest dynamics. The local environment determines competition among the trees, growth, death and regeneration. Therefore, the spatial configuration of the individual trees in a forest stand can provide information about the underlying ecological processes at the site. This thesis focuses on the determination and analysis of the local constellation of individual trees (characterized by species, age, size etc.) in a forest stand. A large number of spatial statistical methods can be applied to this spatial pattern analysis. Besides using some classical statistical methods, I propose two new methods for spatial analysis. First, I develop a new method for the spatial analysis of objects. That approximates each individual tree as a circle, instead of a point, thus minimizing the bias of the classical methods. Finally, I proposed a new method, based on Wavelet Transform, to obtain spatial scale information about the point processes occurring within a study site. By this, this approach goes beyond classical point pattern methods and is innovative.
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The spatial structure of a forest stand is an important signature of forest dynamics. The local environment determines competition among the trees, growth, death and regeneration. Therefore, the spatial configuration of the individual trees in a forest stand can provide information about the underlying ecological processes at the site. This thesis focuses on the determination and analysis of the local constellation of individual trees (characterized by species, age, size etc.) in a forest stand. A large number of spatial statistical methods can be applied to this spatial pattern analysis. Besides using some classical statistical methods, I propose two new methods for spatial analysis. First, I develop a new method for the spatial analysis of objects. That approximates each individual tree as a circle, instead of a point, thus minimizing the bias of the classical methods. Finally, I proposed a new method, based on Wavelet Transform, to obtain spatial scale information about the point processes occurring within a study site. By this, this approach goes beyond classical point pattern methods and is innovative.
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