Mike Robert Strub, Nathaniel Osborne


We introduce a new statistical distribution for modeling tree count in segmented LiDAR point clouds. The new distribution is based on the Poisson distribution as a logical basis since the Poisson is based on the premise of rare events from a large population. The probability a particular tree falls in a given point cloud segment is small and the number of trees is large. The purpose of segmentation is to provide segments that contain a single tree. This implies that a Poisson with deflated probability of zero occurrences and inflated probability of one occurrences is appropriate. LiDAR point cloud data on twenty ground truth plots are used to show the utility of this approach.


Remote sensing, forest inventory, Lambert W


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