Lefsky, M. A.; Cohen, W. B.; Acker, S. A.; Spies, T. A.; Parker, G. G.; Harding, D. 1998. Lidar remote sensing of forest canopy structure and related biophysical parameters at the H.J. Andrews Experimental Forest, Oregon, USA. In: Greer, Jerry Dean, ed. Natural resource management using remote sensing and GIS: Proceedings of the Seventh Forest Service Remote Sensing Applications Conference; 1998 April 6-10; Nassau Bay, TX. Bethesda, MD: American Photogrammetry and Remote Sensing Society: 79-91.
Scanning lidar remote sensing systems have recently become generally availablefor use in ecological applications. Unlike microwave and conventional opticalsensors, lidar sensors directly measure the distribution of vegetation materialalong a vertical axis and can he used to provide three-dimensional
characterizations of vegetation structure. Ecological applications of scanninglidar have previously used uni-dimensional indices of canopy height. A newthree-dimensional approach to interpreting lidar waveforms was developed tocharacterize the total volume of vegetation and empty space within the forestcanopy, and their spatial organization. These aspects of the physical structure ofcanopies have been infrequently measured, either from field or remote methods.We applied this approach to 21 plots in Douglas-fir / Western Hemlock standson the west side of the Cascade range in Oregon, which had coincident lidarmeasurements and field surveys. We were able to predict both biomass and leaf
area index from the volumes of four classes of canopy structure. Thesepredictions were non-asymptotic over a wide range, up to 1200 Mg ha' ofbiomass and an LAI of 12, with 90 % and 88 % of variance explained.respectively. Furthermore, we were able to make accurate estimates of otherstand structure attributes, including the mean and standard deviation of diameterat breast height, the number of stems greater than 100 cm in diameter, andindependent estimates of the basal area of Douglas-fir and Western hemlock. These measurements are directly related to indices of forest stand structuralcomplexity, such as those developed for old-growth forest characterization.