Utvärdering av en subjektiv metod för att skatta mängden trädbiomassa längs vägkanter
Forest biomass is becoming an increasingly important source of renewable energy, and thereby the demand is increasing. There is currently 213 000 km of forest roads in Sweden that could be suitable for biomass harvesting. Harvest of biomass along forest roads both provides biomass and maintains the quality of the roads. Currently, the volume of biomass along roads can only be assessed post harvest, chipping and industry deliverance.
As the decision of whether or not to harvest should preferably be based on more than experience, the TJ-method has been proposed. The TJ-method is a subjective method to quickly determine the dry matter quantity with the assessment being conducted from the roadside. The dry matter quantity is calculated by estimating diameter, height and number of trees. The objective of this study was to evaluate the suitability of using the TJ-method for estimating the dry matter quantity both before and during harvesting. The study evaluated the method in different types of stands and when being used by different people.
This study was performed on three blocks, based on the stands? mean diameter in breast height. Four study units of each block were studied. The in total 12 study units were objectively inventoried and those results were used as reference values.
There were differences in the estimation height and number of trees, mean diameter and dry matter quantity between the blocks in post-harvest estimations. However, the differences were statistically significant only for the former two variables. Estimations for the block with the largest mean diameter gave best results. There were no significant differences between the two trial persons? post-harvest estimations. The TJ-method was more accurate when estimations were made by the machine operator during harvesting than when estimations were made from the roadside before harvesting. There were no significant differences in estimations between different blocks when estimations were made during harvest.
With good training and most importantly, a systematic follow-up of estimations, this method can provide reliable, cost-efficient data that can be used when making decisions on whether to harvest along roads or not.