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Articles containing the keyword 'pre-harvest inventory'

Category: Research article

article id 56, category Research article
Johan Holmgren, Andreas Barth, Henrik Larsson, Håkan Olsson. (2012). Prediction of stem attributes by combining airborne laser scanning and measurements from harvesters. Silva Fennica vol. 46 no. 2 article id 56. https://doi.org/10.14214/sf.56
Keywords: ALS data; pre-harvest inventory; tree detection
Abstract | View details | Full text in PDF | Author Info
In this study, a new method was validated for the first time that predicts stem attributes for a forest area without any manual measurements of tree stems by combining harvester measurements and Airborne Laser Scanning (ALS) data. A new algorithm for automatic segmentation of tree crowns from ALS data based on tree crown models was developed. The test site was located in boreal forest (64°06’N, 19°10’E) dominated by Norway spruce (Picea abies) and Scots Pine (Pinus sylvestris).The trees were harvested on field plots, and each harvested tree was linked to the nearest tree crown segment derived from ALS data. In this way, a reference database was created with both stem data from the harvester and ALS derived features for linked tree crowns. To estimate stem attributes for a tree crown segment in parts of the forest where trees not yet have been harvested, tree stems are imputed from the most similar crown segment in the reference database according to features extracted from ALS data. The imputation of harvester data was validated on a sub-stand-level, i.e. 2–4 aggregated 10 m radius plots, and the obtained RMSE of stem volume, mean tree height, mean stem diameter, and stem density (stems per ha) estimates were 11%, 8%, 12%, and 19%, respectively. The imputation of stem data collected by harvesters could in the future be used for bucking simulations of not yet harvested forest stands in order to predict wood assortments.
  • Holmgren, Swedish University of Agricultural Sciences, Forest Resource Management, Umeå, Sweden E-mail: johan.holmgren@slu.se (email)
  • Barth, The Forestry Research Institute of Sweden, Uppsala, Sweden E-mail: ab@nn.se
  • Larsson, Swedish University of Agricultural Sciences, Forest Resource Management, Umeå, Sweden E-mail: hl@nn.se
  • Olsson, Swedish University of Agricultural Sciences, Forest Resource Management, Umeå, Sweden E-mail: ho@nn.se
article id 543, category Research article
Maarten Nieuwenhuis. (2002). The development and validation of pre-harvest inventory methodologies for timber procurement in Ireland. Silva Fennica vol. 36 no. 2 article id 543. https://doi.org/10.14214/sf.543
Keywords: pre-harvest inventory; simulation; dynamic programming; value maximisation; optimal crosscutting
Abstract | View details | Full text in PDF | Author Info
This article describes the development and validation of a decision-support system for sawmill wood procurement, dealing specifically with the integration of the pre-harvest inventory procedures, site-specific dbh/height models and a generic taper equation, with a crosscutting simulator. The crosscutting simulation program faithfully mimics the process of cut-to-length harvesting and provides detailed information on the potential volume, logs count and diameter distributions for different log assortment specifications. Four data sets, consisting of a total of 4153 diameter and height measurements, were used in the validation process. The sites included two Sitka spruce clearfells, a Sitka spruce thinning and a Norway spruce clearfell. The evaluation process has shown that the developed decision-support system produced accurate results for a wide range of stand types, as long as sufficient large data sets were used, and that it provides the wood procurement manager of a sawmill with an efficient means of gaining a comprehensive insight into the yield potential of standing timber lots and, as such, represents a valuable aid to timber procurement and production planning.
  • Nieuwenhuis, University College Dublin, Dept. of Forestry, Belfield, Dublin 4, Ireland E-mail: maarten.nieuwenhuis@ucd.ie (email)

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