Rethinking Productivity Evaluation in Precision Forestry through Dominant Height and Site Index Measurements Using Aerial Laser Scanning LiDAR Data

dc.contributor.authorRaigosa-García, Ivánen
dc.contributor.authorRathbun, Leah C.en
dc.contributor.authorCook, Rachel L.en
dc.contributor.authorBaker, Justin S.en
dc.contributor.authorCorrao, Mark V.en
dc.contributor.authorSumnall, Matthew J.en
dc.date.accessioned2024-06-26T13:35:38Zen
dc.date.available2024-06-26T13:35:38Zen
dc.date.issued2024-06-07en
dc.date.updated2024-06-26T13:22:50Zen
dc.description.abstractOptimizing forest plantation management has become imperative due to increasing forest product demand, higher fertilization and management costs, declining land availability, increased competition for land use, and the growing demands for carbon sequestration. Precision forestry refers to the ability to use data acquired with technology to support the forest management decision-making process. LiDAR can be used to assess forest metrics such as tree height, topographical position, soil surface attributes, and their combined effects on individual tree growth. LiDAR opens the door to precision silviculture applied at the tree level and can inform precise treatments such as fertilization, thinning, and herbicide application for individual trees. This study uses ALS LiDAR and other ancillary data to assess the effect of scale (i.e., stand, soil type, and microtopography) on dominant height and site index measures within loblolly pine plantations across the southeastern United States. This study shows differences in dominant height and site index across soil types, with even greater differences observed when the interactions of microtopography were considered. These results highlight how precision forestry may provide a unique opportunity for assessing soil and microtopographic information to optimize resource allocation and forest management at an individual tree scale in a scarce higher-priced fertilizer scenario.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRaigosa-García, I.; Rathbun, L.C.; Cook, R.L.; Baker, J.S.; Corrao, M.V.; Sumnall, M.J. Rethinking Productivity Evaluation in Precision Forestry through Dominant Height and Site Index Measurements Using Aerial Laser Scanning LiDAR Data. Forests 2024, 15, 1002.en
dc.identifier.doihttps://doi.org/10.3390/f15061002en
dc.identifier.urihttps://hdl.handle.net/10919/119525en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleRethinking Productivity Evaluation in Precision Forestry through Dominant Height and Site Index Measurements Using Aerial Laser Scanning LiDAR Dataen
dc.title.serialForestsen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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