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dc.contributor.authorPascual, Adrián
dc.contributor.authorPukkala, Timo
dc.contributor.authorMiguel Magaña, Sergio de
dc.contributor.authorPesonen, Annukka
dc.contributor.authorPackalen, Petteri
dc.date.accessioned2019-03-14T10:25:05Z
dc.date.available2019-03-14T10:25:05Z
dc.date.issued2019
dc.identifier.issn1612-4669
dc.identifier.urihttp://hdl.handle.net/10459.1/65951
dc.description.abstractThe purpose of this study was to assess the effect of using alternative types of forest inventory units (FIUs) in multi-objective forest planning. The research was carried out in a Mediterranean forest area in central Spain. The study area was divided, alternatively, into pixels (square cells) and segments of two different sizes (small and large), which represented the tested FIU types. Airborne laser scanning data (ALS) and field sample plots were combined using the area-based approach to estimate forest attributes for each FIU. Dynamic treatment units were created using cellular automaton optimization aiming at maximizing timber production during a 60-year plan with periodical even-flow cuttings both with and without the aim of creating aggregated harvest blocks. The hypothesis was that the use of segments would enhance the clustering of harvests, as compared to cells, and provide dynamic treatment units more suitable for forestry practice. The results showed that segment-based planning created compact harvest blocks even without the use of spatial objective variables in optimization. The spatial layout of the solution for large segments was the most efficient in the absence of spatial objective variables. The FIU type that performed the best in maximizing timber production was the small segments. For the three tested FIU types, the inclusion of spatial objective variables further improved the clustering of harvests, especially during the latter half of the 60-year planning period. Segmentation acted as a first-phase clustering that made spatial optimization easier and faster. In the case of square cells, the clustering of harvests was greatly improved by the inclusion of spatial goals. The forest planning system and the spatial optimization method proposed in this study maximize the utility of fine-grained ALS data.ca_ES
dc.description.sponsorshipOpen access funding provided by University of Eastern Finland (UEF) including Kuopio University Hospital. This research was supported by the University of Eastern Finland, School of Forest Sciences and research consortium projects FORBIO (Proj. 14970) and ADAPT (Proj. 14907), funded by the Academy of Finland and led by Prof. Heli Peltola, at the School of Forest Sciences, University of Eastern Finland (UEF). Sergio de-Miguel was supported by the European Union’s Horizon 2020 MultiFUNGtionality Marie Sklodowska-Curie (IF-EF No 655815).ca_ES
dc.language.isoengca_ES
dc.publisherSpringerca_ES
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1007/s10342-018-1157-5ca_ES
dc.relation.ispartofEuropean Journal of Forest Research, 2019, vol. 138, p. 111-123ca_ES
dc.rightscc-by, (c) Pacual et al., 2018ca_ES
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectSpatial forest planningca_ES
dc.subjectOptimizationca_ES
dc.subjectDecision-makingca_ES
dc.subjectAirborne laser scanningca_ES
dc.titleInfluence of size and shape of forest inventory units on the layout of harvest blocks in numerical forest planningca_ES
dc.typeinfo:eu-repo/semantics/articleca_ES
dc.identifier.idgrec028426
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_ES
dc.identifier.doihttps://doi.org/10.1007/s10342-018-1157-5
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/655815/EU/MultiFUNGtionalityca_ES


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