Original scientific paper
Impact of Slope on Productivity of a Self-levelling Processor
Martin Strandgard
orcid.org/0000-0002-4657-1322
; Australia Forest Operations Research Alliance (AFORA) University of the Sunshine Coast 500 Yarra Boulevard 3121 Richmond AUSTRALIA
Muhammad Alam
; University of Melbourne 500 Yarra Boulevard 3121 Richmond AUSTRALIA
Rick Mitchell
; Australia Forest Operations Research Alliance (AFORA) University of the Sunshine Coast 35 Shorts Place 6330 Albany AUSTRALIA
Abstract
Slope is a major factor affecting forest harvesting machine productivity. As ground-based harvesting methods are generally cheaper than the alternatives, forest managers need to know when ground-based harvesting equipment can be used on sloping sites.
The study objective was to determine the effect of slope on the productivity, cycle time and elemental times of a Valmet 450 FXL self-levelling processor processing a 24 year-old, unthinned radiata pine plantation previously felled and stacked by a feller-buncher.
The study site slope was estimated using a LiDAR (Light Detection and Ranging) derived digital terrain model and classified using the regional terrain classification system. Study trees were selected from areas predominantly in the hilly (12–19°) and steep (20–26°) slope classes, as these classes made up the majority of the study site area. In contrast to previous research, no significant differences were found between the processor productivity, cycle time and elemental times (moving/positioning, swinging and processing) between the slope classes. This was believed to result from the processor working well within its capabilities processing the relatively small trees on the study site. Other important factors may have included that the trees were pre-felled by a feller-buncher and placed in high density rows with their butt ends aligned, which minimised the processor boom and track movements, and that steep slope trees were selected from areas at the lower end of the steep slope class (20–23°). Further research is needed to determine whether the processor productivity would be significantly lower when processing larger trees on steeper slopes.
Keywords
self-levelling; processor; slope; productivity; radiata pine; LiDAR; Australia
Hrčak ID:
127002
URI
Publication date:
15.9.2014.
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