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

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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.
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Keywords: Boolean model; airborne laser scanning; canopy height; forest inventory; marked point process; maximum likelihood; porosity; size distribution; stand density; tree height

Document Type: Research Article

Publication date: 2009-10-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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