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A systematic approach for using lidar intensity to detect forest structure.

Lidar intensity, a quantity analogous to backscatter, has yet to be fully exploited as an
information source in the characterization of coniferous forests. Intensity images appear
noisy due to (1) dynamic survey geometry, and (2) complex laser interactions in a
forested environment. The nature of these issues are explored, and a systematic procedure
for processing, visualizing, and normalizing the intensity data is presented. Despite high
variability among neighbouring intensity values, the data are inherently spatially
structured. Results from an investigation into the spatial pattern of intensity demonstrate
that (1) the scale and variability of global estimates of spatial autocorrelation derived
from raw intensity (point) data were markedly different between stands of different age,
and these differences were driven by the canopy and gap structure within each individual
stand, and (2) the magnitude of local estimates of spatial autocorrelation varied with
canopy height, and, particularly in old growth stands, these magnitudes are linked to
compositional factors such as species.

Identiferoai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/1249
Date12 November 2008
CreatorsLangford, Jaden Orion
ContributorsNiemann, K. O.
Source SetsUniversity of Victoria
LanguageEnglish, English
Detected LanguageEnglish
TypeThesis
RightsAvailable to the World Wide Web

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