Predicting factual sawlog volumes in Scots pine dominated forests using airborne laser scanning data

Abstract

The aim in the study was to compare alternatives for the prediction of factual sawlog volumes using airborne laser scanning (ALS) data in Scots pine ( L.) dominated forests in eastern Finland. Accurate estimates of factual sawlog volume are desirable to ease the planning of harvesting operations. The factual sawlog volume of pines was derived from visual bucking, i.e. a procedure where the defects were located on each stem during sample plot measurements. For other species, the theoretical sawlog volume was considered also as the factual sawlog volume due to data restrictions. We predicted factual sawlog volume with eight alternatives that were based on either linear mixed-effects models or k-nearest neighbour imputations. An existing sawlog reduction model, commonly used in Finland, was also tested individually and combined with a number of the alternatives, and site type information was also utilised. Model fitting and prediction was implemented at the 15 × 15 m level, but accuracy was assessed at the 30 × 30 m level. The relative root mean squared error (RMSE%) values for the factual sawlog volume predictions varied between 20.9% and 33.5%, and the best accuracy was obtained with a linear mixed-effects model. These results indicate that factual sawlog volumes in Scots pine dominated forests can be predicted with reasonable accuracy with ALS data.Pinus sylvestris

From comprehensive field inventories to remotely sensed wall-to-wall stand attribute data — a brief history of management inventories in the Nordic countries

“…Different ground-based and mobile-based scanners can also take some tree quality aspects into consideration (e.g., Kretschmer et al 2013;Pyörälä et al 2019). Tree quality aspects can also be included in field measurements, field calibrations of existing quality models may be conducted, or harvester information may be utilized (Karjalainen et al 2019(Karjalainen et al , 2020. In addition, there have been experimental UAV data acquisitions under the canopy, thereby providing critical information to improve tree stem prediction and understory characterization (Hyyppä et al 2020a).…”

Field calibration of merchantable and sawlog volumes in forest inventories based on airborne laser scanning

“…Then, laborious and time-consuming visual bucking to estimate tree level sawlog volumes (e.g. Karjalainen et al 2019) would not be needed during field work.…”

“…The resulting RMSE% value for sawlog volume was 18 % at the stand-level. Karjalainen et al (2019) used visually bucked Scots pines in an ABA, which resulted in a RMSE% value of 21 % for 30 m × 30 m cells.…”

Assessing and mitigating systematic errors in forest attribute maps utilizing harvester and airborne laser scanning data

“…Har-vester data are a potential alternative to traditional field data in forest inventories relying on ALS. In addition to the economic efficiency of data collection, harvester data are also attractive since these data include bucking information (Bollands ås et al 2013;Karjalainen et al 2019;Räty et al 2021b). Harvesters also enable the collection of data from large-area units that are too expensive to measure using traditional field measurements.…”