Classification of Needle Loss of Individual Scots Pine Trees by Means of Airborne Laser Scanning

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dc.contributor.author Kantola, Tuula
dc.contributor.author Vastaranta, Mikko
dc.contributor.author Lyytikäinen-Saarenmaa, Päivi
dc.contributor.author Holopainen, Markus
dc.contributor.author Kankare, Ville
dc.contributor.author Talvitie, Mervi
dc.contributor.author Hyyppä, Juha
dc.date.accessioned 2016-01-21T12:37:01Z
dc.date.available 2016-01-21T12:37:01Z
dc.date.issued 2013
dc.identifier.citation Kantola , T , Vastaranta , M , Lyytikäinen-Saarenmaa , P , Holopainen , M , Kankare , V , Talvitie , M & Hyyppä , J 2013 , ' Classification of Needle Loss of Individual Scots Pine Trees by Means of Airborne Laser Scanning ' , Forests , vol. 4 , no. 2 , pp. 386-403 . https://doi.org/10.3390/f4020386
dc.identifier.other PURE: 29018943
dc.identifier.other PURE UUID: f90c7de3-5716-4967-8760-533944829dcb
dc.identifier.other WOS: 000320773200011
dc.identifier.other Scopus: 84883294625
dc.identifier.other ORCID: /0000-0003-1884-3084/work/41082542
dc.identifier.other ORCID: /0000-0002-1683-016X/work/30288984
dc.identifier.other ORCID: /0000-0001-6552-9122/work/29615042
dc.identifier.uri http://hdl.handle.net/10138/159627
dc.description.abstract Forest disturbances caused by pest insects are threatening ecosystem stability, sustainable forest management and economic return in boreal forests. Climate change and increased extreme weather patterns can magnify the intensity of forest disturbances, particularly at higher latitudes. Due to rapid responses to elevating temperatures, forest insect pests can flexibly change their survival, dispersal and geographic distributions. The outbreak pattern of forest pests in Finland has evidently changed during the last decade. Projection of shifts in distributions of insect-caused forest damages has become a critical issue in the field of forest research. The Common pine sawfly (Diprion pini L.) (Hymenoptera, Diprionidae) is regarded as a significant threat to boreal pine forests. Defoliation by D. pini has resulted in severe growth loss and mortality of Scots pine (Pinus sylvestris L.) (Pinaceae) in eastern Finland. In this study, tree-wise defoliation was estimated for five different needle loss category classification schemes and for 10 different simulated airborne laser scanning (ALS) pulse densities. The nearest neighbor (NN) approach, a nonparametric estimation method, was used for estimating needle loss of 701 Scots pines, using the means of individual tree features derived from ALS data. The Random Forest (RF) method was applied in NN-search. For the full dense data (~20 pulses/m2), the overall estimation accuracies for tree-wise defoliation level varied between 71.0% and 86.5% (kappa-values of 0.56 and 0.57, respectively), depending on the classification scheme. The overall classification accuracies for two class estimation with different ALS pulse densities varied between 82.8% and 83.7% (kappa-values of 0.62 and 0.67, respectively). We conclude that ALS-based estimation of needle losses may be of acceptable accuracy for individual trees. Our method did not appear sensitive to the applied pulse densities. en
dc.format.extent 18
dc.language.iso eng
dc.relation.ispartof Forests
dc.rights cc_by
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject 4112 Forestry
dc.subject ALS
dc.subject Defoliation
dc.subject Diprion pini
dc.subject Forest disturbances
dc.subject Effect of pulse density
dc.subject LiDAR
dc.subject Random Forest
dc.title Classification of Needle Loss of Individual Scots Pine Trees by Means of Airborne Laser Scanning en
dc.type Article
dc.contributor.organization Department of Forest Sciences
dc.contributor.organization Laboratory of Forest Resources Management and Geo-information Science
dc.contributor.organization Forest Ecology and Management
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.3390/f4020386
dc.relation.issn 1999-4907
dc.rights.accesslevel openAccess
dc.type.version publishedVersion
dc.identifier.url http://www.mdpi.com/1999-4907/4/2/386

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