Track-Monitoring and Analyzing Machine Clearances during Wood Forwarding

Abstract

This article reports on track-monitoring and analyzing machine clearances during wood forwarding across seasons and weather, using ultrasonic distance sensors in combination with time-stamped GPS xy locations, at 10 sec intervals. The resulting data, obtained from 54 harvesting blocks, were analyzed by machine type (two wood forwarders and one grapple skidder), stand type (softwood plantation versus natural hardwood stands), month, slope, cartographic depth-to-water (DTW) classes, number of passes along track, and machine speed. For the most part, clearances were highly variable, due to passing over stumps, rocks, harvest slash, brushmats, ruts, and snow cover when present. This variability was on average greater for the lighter-weight wood forwarders than for the heavier-weight skidder, with the former mostly moving along equally spaced lines on brushmats, while the paths of the latter spread away from central wood-landing sites. In terms of trends, machines moved 1) more slowly on wet ground, 2) faster during returning than forwarding, and 3) fastest along wood-landing roads, as to be expected. Low clearances were most notable during winter on snow-covered ground, and on non-frozen shallow DTW and wet multiple-pass ground. During dry weather conditions, clearances also increased from low-pass tracks to multi-pass tracks due to repeat soil compaction of broadened tracks. These results are presented block-by-block and by machine type. Each block-based clearance frequency pattern was quantified through regression analysis and using a gamma probability distribution function.

Soil Trafficability Forecasting

“…The resulting GPS data were processed to determine the number of passes per same track using point buffering and overlapping tools (Buja, 2012). Studies have shown that the number of wood-forwarding passes affects soil structure, compaction, and rut depth (Eliasson, 2005;Ampoorter et al, 2007;Farzaneh et al, 2012;Jones et al, 2018). Some studies have looked at mitigating multiple-pass soil rutting using brushmats (McDonald & Sexias, 1997;Labelle et al, 2015).…”

“…Studies have also shown that Table 3. Machine specifications (Jones et al, 2018 lower tire footprint areas due to increasing tire pressure increases rutting (Raper et al, 1995;Saarilahti & Antilla, 1999;Saarilahti, 2002b;Jun et al, 2004;Affleck, 2005;Sakai et al, 2008).…”

“…5) GPS-recorded machine-clearance pattern, spaced at 10 sec intervals along each wood-forwarding track. The generation of these data was described by Jones et al (2018). (Table 2) in the fall of 2014, as described in Jones and Arp (2019).…”

“…Wood-forwarding rut depths were determined at GPS-recorded intervals along the tracks. The number of passes along the tracks were obtained from the GPS-tracked wood-forwarding machine-clearance records (Jones et al, 2018) through counting the number of passes per same track using digital point buffering and overlapping tools (Buja, 2012).…”

Analyzing and Projecting Soil Moisture and Cone Penetrability Variations in Forest Soils

“…Doing so would likely increase the significance by which projected sand, clay, organic matter, coarse fragments and bulk density gain significance as MC and CI predictors. Vega-Nieva et al (2009) and Jones et al (2018). In turn, such projections can be used to evaluate existing traffic-induced soil disturbance impacts as demonstrated by Campbell et al (2013).…”