Mapping percent canopy cover using individual tree- and area-based procedures that are based on airborne LiDAR data: Case study from an oak-hickory-pine forest in the USA

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dc.contributor.authorVatandaşlar, Can
dc.contributor.authorLee, Taeyoon
dc.contributor.authorBettinger, Pete
dc.contributor.authorUçar, Zennure
dc.contributor.authorStober, Jonathan
dc.contributor.authorPeduzzi, Alicia
dc.date.accessioned2024-11-26T12:16:51Z
dc.date.available2024-11-26T12:16:51Z
dc.date.issued2024
dc.departmentAÇÜ, Orman Fakültesi, Orman Mühendisliği Bölümüen_US
dc.description.abstractCanopy cover (CC) is the proportion of a forest floor covered by the vertical projection of tree crowns. Recently, it has become common to utilize LiDAR (light detection and ranging) canopy metrics to estimate CC over large areas. However, these metrics are primarily related to canopy density rather than the specific definition of CC. Here, two processes that employed individual tree segmentation (ITS) and area-based procedures based on LiDAR data are presented to estimate CC across the Talladega Division of the Talladega National Forest (93,694 ha) at the plot, stand, and landscape levels. The two analytical procedures were assessed using the results of a plot/grid method as a reference dataset, which focused on CC estimates within 255 field measurement fixed-area sample plots. The accuracy of a third process, employing an imagery-based visual CC assessment, was also compared against the two procedures and the reference dataset. The LiDAR-based analytical procedures were able to provide estimates of CC with an RMSE of approximately 15 %, which is acceptable for landscape-level assessments. Based on the results of this study, we conclude that CC maps, when created using LiDAR data, may be suitable for various operational tasks such as assessing the impact of forest disturbances and helping to determine the habitat suitability for certain wildlife species.
dc.identifier.doi10.1016/j.ecolind.2024.112710
dc.identifier.issn1470160X
dc.identifier.scopusqualityQ1
dc.identifier.urihttp://dx.doi.org/10.1016/j.ecolind.2024.112710
dc.identifier.urihttps://hdl.handle.net/11494/5026
dc.identifier.volume167en_US
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherElsevier B.V.en_US
dc.relation.ispartofEcological Indicators
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAerial Imageryen_US
dc.subjectAirborne Laser Scanning (ALS)en_US
dc.subjectArea-Based Approach (ABA)en_US
dc.subjectCrown Closureen_US
dc.subjectIndividual Tree Detection (ITD)en_US
dc.subjectPhoto Interpretationen_US
dc.titleMapping percent canopy cover using individual tree- and area-based procedures that are based on airborne LiDAR data: Case study from an oak-hickory-pine forest in the USAen_US
dc.typeArticle

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