Modeling stump biomass of stands using harvester measurements for adaptive energy wood procurement systems

Published Date
Energy
September 2010, Vol.35(9):3717–3721, doi:10.1016/j.energy.2010.05.017

Author 

• Lauri Vesa ^a
• Teijo Palander ^b,,

• aForestCalc Consulting Oy Ltd., 80230 Joensuu, Finland
• bSchool of Forest Sciences, University of Eastern Finland, 80100 Joensuu, Finland

Received 21 January 2010. Revised 5 May 2010. Accepted 8 May 2010. Available online 11 June 2010. 

Abstract

The value and volumes of industrial stump fuel supply are increasing for energy production. Accurate estimates of aboveground and belowground biomass of trees are important when estimating the potential of stumps as a bioenergy source. In this study two stump biomass equations were adapted and tested using them as calibrated stump biomass models computed as the cumulative sum by a local stand. In addition, variables derived from stem measurements of the forest harvester data were examined to predict stump biomass of a stand by applying regression analysis. The true stump yield (dry weight) was used as the reference data in the study. Both biomass models performed well (adjusted R² ˜ 0.84) and no advance was found in using other stem dimensions as independent variables in the model. The stand-level model can be used in innovative stump biomass prediction tools for increasing efficiency of energy wood procurement planning to stands within a certain area. In practice, wood procurement managers would need to adapt developed system and decide whether the degree of accuracy/precision provided by the models is acceptable in their local stand harvesting conditions.

Keywords

Energy wood

Planning system

Forest harvester

Adaptive methods

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Nomenclature

B_stump

total yield of stump biomass, kg/stand (dry weight)

h_u

length of the top part of a stem, mm

d_stump

diameter at stump height, mm

d_1.3

diameter at breast height, mm

h_k

measured length of the stem, mm

d_p

top diameter, under bark, cm

ln

natural logarithm

n

number of selected trees in stand

ns

number of stands

Y_i

observed biomass values of stand i

Ŷ_i

predicted biomass values of stand i

e_i

random effect in stand i

Fig. 1.

Fig. 2.

Fig. 3.

Fig. 4.

 Table 1

Table 1.

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