Description and evaluation of Prehas software for pre-harvest assessment of timber assortments

Abstract

Prehas is a decision support tool for assessing the amount and value of harvestable timber, including predictions of timber assortment recovery, length-diameter distribution of logs, and value recovery. Predictions are based on previously collected cut-to-length harvester stem data (stm-data), which is stored by the software as a stem database, and a non-parametric k-MSN method. Using easily achievable search variables, Prehas produces stem group estimates, including stem diameters at 10 cm intervals for each stem. This stem group can be bucked using a bucking simulator (included in Prehas) to achieve the estimates of timber assortment recovery, value, and log length-diameter distribution. Prehas has three versions: Prehas-International, Prehas-Scotland, and Prehas-Finland, of which the latter is also capable of predicting the technical quality of stems to be used in bucking simulations. The software includes routines for the user to collect and save their own stm-data representing local forests. This article describes the structure and methodology of Prehas.

To assess the performance of Prehas, a test was conducted using the empirical data collected for measurements of dimensions and quality of trees from sample plots. The data consisted of 61 stands located in south-eastern Finland including commercial clear-cutting stands in private and state forests. Prehas’s predictions were slightly more reliable than those of the compared timber assortment recovery regression models for southern Finland.

Keywords:

• pre-harvest assessment
• k-MSN method
• simulation
• value
• quality
• bucking

Acknowledgements

The development of Prehas was conducted in the Developing the Scots Pine Resource project funded by EU’s Northern Periphery Programme. The authors thank the anonymous peer reviewers for improvements to the manuscript.