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

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dc.contributor.authorLangford, Jaden Orion
dc.contributor.supervisorNiemann, K. O.
dc.date.accessioned2008-11-12T19:45:24Z
dc.date.available2008-11-12T19:45:24Z
dc.date.copyright2006en_US
dc.date.issued2008-11-12T19:45:24Z
dc.degree.departmentDepartment of Geography
dc.degree.levelMaster of Science M.Sc.en_US
dc.description.abstractLidar 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.en_US
dc.identifier.urihttp://hdl.handle.net/1828/1249
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectRadaren_US
dc.subjectForestryen_US
dc.subject.lcshUVic Subject Index::Sciences and Engineering::Agriculture::Forests and forestryen_US
dc.titleA systematic approach for using lidar intensity to detect forest structure.en_US
dc.typeThesisen_US

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