Abstract

Modern computerization facilitates data-gathering from forest machines, and offers new opportunities to develop models for predicting productivity in forest harvest operations. In this study, we analyze the productivity of cut-to-length harvesting and forwarding in thinning and final felling using a routinely recorded followup dataset. The data originate from over 700 machines that, over a 3-year period, harvested and forwarded more than 20 million m³ of round-wood from upwards of 20 thousand stands, making the dataset larger than any that has previously been used for productivity modelling. Results comprise a range of stand-based productivity models of varying complexity for both harvesters and forwarders. Mean stem size was the most influential variable for harvesting productivity: modelling based on mean stem size explained 57.6% of the variance in thinnings and 55.3% in final fellings. However, accurate predictions of forwarding productivity required the simultaneous consideration of several variables. For instance, modelling of forwarder productivity based on the variables mean stem size, mean extraction distance and forwarder load capacity explained 26.4% of the variance in thinnings and 35.2% in final fellings. Results should be of interest to both practitioners and researchers interested in the study and modelling of forest operations.

Keywords

productivity, cut-to-length, harvester, forwarder, regression model

Published in

International Journal of Forest Engineering
2014, Volume: 25, number: 3, pages: 179-200

SLU Authors

• Lindroos, Ola

  • Department of Forest Biomaterials and Technology, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Work Sciences
Forest Science


Publication identifier

DOI: https://doi.org/10.1080/14942119.2014.974309

Permanent link to this page (URI)

https://res.slu.se/id/publ/63170