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dc.contributor.authorPackalen, Petteri
dc.contributor.authorStrunk, Jacob
dc.contributor.authorPackalen, Tuula
dc.contributor.authorMaltamo, Matti
dc.contributor.authorMehtätalo, Lauri
dc.date.accessioned2020-01-08T08:12:37Z
dc.date.available2020-01-08T08:12:37Z
dc.date.issued2019
dc.identifier.urihttps://erepo.uef.fi/handle/123456789/7887
dc.description.abstractIn an Area Based Approach (ABA) to forest inventories using Airborne Laser Scanning (ALS) data, the sample plot size may vary or the cell size may differ from the plot size. Although this resolution mismatch may cause bias and increase in prediction error, it has not been thoroughly studied. The aim of this study was to clarify the meaning of resolution dependence in ABA, and to further identify its causal factors and quantify their effects. In general, a number of factors contribute to resolution dependence in ABA forest inventories, including the varying point density of the ALS data, the type of response variable, how the predictor variables are computed, and the properties of the prediction model. For quantification, we used field plots with mapped tree locations, which enabled the generation of different sized sample plots inside a larger plot. Plot level above ground biomass (AGB) was the response variable employed in all the models. The error rate seemed to increase when the prediction plots were larger than the fitting plots, and vice versa. The maximum BIAS was 1.50% and the maximum change of RMSE compared to its value in native resolution was 0.97% when there was a 4-fold difference in resolution. This indicates that the resolution effect is small in most real-world use cases, however, resolution effect should be carefully considered in ALS-assisted large area inventories that target unbiased estimates of forest parameters.
dc.language.isoenglanti
dc.publisherElsevier BV
dc.relation.ispartofseriesRemote sensing of environment
dc.relation.urihttp://dx.doi.org/10.1016/j.rse.2019.01.022
dc.rightsCC BY-NC-ND https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectscale dependence
dc.subjectresolution invariance
dc.subjectairborne laser scanning
dc.subjectforest inventory
dc.subjectlidar
dc.titleResolution dependence in an area-based approach to forest inventory with airborne laser scanning
dc.description.versionfinal draft
dc.contributor.departmentSchool of Forest Sciences, activities
dc.contributor.departmentSchool of Computing, activities
uef.solecris.id61370614en
dc.type.publicationTieteelliset aikakauslehtiartikkelit
dc.rights.accessrights© Elsevier Inc
dc.relation.doi10.1016/j.rse.2019.01.022
dc.description.reviewstatuspeerReviewed
dc.format.pagerange192-201
dc.relation.issn0034-4257
dc.relation.volume224
dc.rights.accesslevelopenAccess
dc.type.okmA1
uef.solecris.openaccessEi


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