Estimating Forest Attributes Using Observations of Canopy Height: A Model-Based Approach

Abstract

Abstract An airborne laser scanner can be used to make observations of canopy height at given locations within a forest stand. In recent years, foresters have developed methods to extract information on forest attributes, such as stand density and size distribution of the trees, from laser data for forest inventory purposes. These methods are based on empirical relationships rather than on theory about how observations are generated by tree canopies. We recover the relationship between canopy height and forest attributes, based on assumptions about the shape of a single tree crown, the distribution of tree height, and the spatial distribution of tree locations. This work improves our understanding of how stand characteristics are related to observations collected by airborne laser scanners and links the problem to the theory of germ-grain models and random closet sets in spatial statistics. Furthermore, we use the derived relationship to develop a model-based approach for estimating stand density and distribution of tree heights using observations of canopy height. A simulation study showed that the method is capable of producing fairly accurate estimates for the number of stems and mean tree height, yielding only slight biases in mean tree height and stand density.