Characterizing vertical forest structure using small-footprint airborne LiDAR

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dc.contributor.authorZimble, D.en
dc.contributor.authorEvans, D.en
dc.contributor.authorCarlson, G.en
dc.contributor.authorParker, R.en
dc.contributor.authorGrado, S.en
dc.contributor.authorGerard, Patrick D.en
dc.contributor.departmentSustainable Agriculture and Natural Resource Management (SANREM) Knowledgebaseen
dc.coverage.spatialIntermountain West regionen
dc.coverage.spatialUnited Statesen
dc.date.accessioned2016-04-19T18:55:30Zen
dc.date.available2016-04-19T18:55:30Zen
dc.date.issued2003en
dc.description.abstractCharacterization of forest attributes at fine scales is necessary to manage terrestrial resources in a manner that replicates, as closely as possible, natural ecological conditions. In forested ecosystems, management decisions are driven by variables such as forest composition, forest structure (both vertical and horizontal), and other ancillary data (i.e., topography, soils, slope, aspect, and disturbance regime dynamics). Vertical forest structure is difficult to quantify and yet is an important component in the decision-making process. This study investigated the use of light detection and ranging (LiDAR) data for classifying this attribute at landscape scales for inclusion into decision-support systems. Analysis of field-derived tree height variance demonstrated that this metric could distinguish between two classes of vertical forest structure. Analysis of LiDAR-derived tree height variance demonstrated that differences between single-story and multistory vertical structural classes could be detected. Landscape-scale classification of the two structure classes was 97% accurate. This study suggested that within forest types of the Intermountain West region of the United States, LiDAR-derived tree heights could be useful in the detection of differences in the continuous, nonthematic nature of vertical forest structure with acceptable accuracies.en
dc.format.mimetypeapplication/pdfen
dc.identifier1000en
dc.identifier.citationRemote Sensing of Environment 87(2-3): 171-182en
dc.identifier.doihttps://doi.org/10.1016/S0034-4257(03)00139-1en
dc.identifier.issn0034-4257en
dc.identifier.other1000_00012.pdfen
dc.identifier.urihttp://hdl.handle.net/10919/65879en
dc.language.isoen_USen
dc.publisherAmsterdam, Netherlands: Elsevier Science B.V.en
dc.rightsIn Copyrighten
dc.rights.holderCopyright 2003 by Elsevier Inc. All rights reserveden
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectEcosystemen
dc.subjectSemiarid zonesen
dc.subjectForest managementen
dc.subjectArid zonesen
dc.subjectForest ecosystemsen
dc.subjectRemote sensingen
dc.subjectResource management toolsen
dc.subjectNatural resource managementen
dc.subjectTree measurementen
dc.subjectLiDARen
dc.subjectForest structureen
dc.subjectIntermountain Westen
dc.subjectEcosystemen
dc.titleCharacterizing vertical forest structure using small-footprint airborne LiDARen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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