The significance of above-ground biomass, moisture content and mechanical properties of peat layer on the bearing capacity of ditched pine bogs

Uusitalo, Jori; Ala‐Ilomäki, Jari

doi:10.14214/sf.993

Cited by 32 publications

(38 citation statements)

References 16 publications

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“…Ruts are formed when the loading exerted by the forest vehicle exceeds the strength of the soil [12][13][14]. The bearing capacity depends on various static and dynamic factors: e.g., soil type, root density, slope and other micro-topographic water dynamics and frost state.…”

Section: Introductionmentioning

confidence: 99%

“…The bearing capacity depends on various static and dynamic factors: e.g., soil type, root density, slope and other micro-topographic water dynamics and frost state. As a result, both the spatial and temporal variation in trafficability is extremely large [14,15]. An easily collected and extensive dataset on rut depths that covers field measurements over several test sites and various weather conditions is thus needed for any attempts to model forest terrain trafficability [16].…”

Section: Introductionmentioning

confidence: 99%

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Estimating the Rut Depth by UAV Photogrammetry

et al. 2017

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Abstract:The rut formation during forest operations is an undesirable phenomenon. A methodology is being proposed to measure the rut depth distribution of a logging site by photogrammetric point clouds produced by unmanned aerial vehicles (UAV). The methodology includes five processing steps that aim at reducing the noise from the surrounding trees and undergrowth for identifying the trails. A canopy height model is produced to focus the point cloud on the open pathway around the forest machine trail. A triangularized ground model is formed by a point cloud filtering method. The ground model is vectorized using the histogram of directed curvatures (HOC) method to produce an overall ground visualization. Finally, a manual selection of the trails leads to an automated rut depth profile analysis. The bivariate correlation (Pearson's r) between rut depths measured manually and by UAV photogrammetry is r = 0.67. The two-class accuracy a of detecting the rut depth exceeding 20 cm is a = 0.65. There is potential for enabling automated large-scale evaluation of the forestry areas by using autonomous drones and the process described.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimating the Rut Depth by UAV Photogrammetry

et al. 2017

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“…There is, however, a problem in the utilization of the timber resources in the drained sites. The generally poor bearing capacity of peat makes harvest conditions more demanding than those in the upland sites (Uusitalo and Ala-Ilomäki 2013). Due to the poor support of peat for harvesting machines, peatland harvesting has been traditionally done in seasons when the soil is frozen to prevent machines from sinking.…”

Section: Introductionmentioning

confidence: 99%

Performance of weather parameters in predicting growing season water table depth variations on drained forested peatlands – a case study from southern Finland

Hökkä¹,

Uusitalo²,

Lindeman³

et al. 2016

Silva Fenn.

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Highlights• Four-week precipitation and evapotranspiration explain much of drained peatland water table depth variation during a growing season. AbstractThe amount of water in peat soil is one factor affecting its bearing capacity, which is a crucial aspect in planning peatland timber harvesting operations. We studied the influence of weather variables on the variation of drained peatland growing season water conditions, here the ground water table depth (WTD). WTD was manually monitored four times in 2014 and three times in 2015 in 10-30 sample plots located in four drained peatland forests in south-western Finland. For each peatland, precipitation and evapotranspiration were calculated from the records of the nearest Finnish Meteorological Institute field stations covering periods from one day to four weeks preceding the WTD monitoring date. A mixed linear model was constructed to investigate the impact of the weather parameters on WTD. Precipitation of the previous four-week period was the most important explanatory variable. The four-week evapotranspiration amount was interacting with the Julian day showing a greater effect in late summer. Other variables influencing WTD were stand volume within the three-metre radius sample plot and distance from nearest ditch. Our results show the potential of weather parameters, specifically that of the previous four-week precipitation and evapotranspiration, for predicting drained peatland water table depth variation and subsequently, the possibility to develop a more general empirical model to assist planning of harvesting operations on drained peatlands.

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“…Consequently, peatlands consist nowadays one third of the Finnish forestry area and one fourth of the growing stock volume (Ala-Ilomäki et al, 2011). In increasing the wood harvesting, more intensive utilization of drained peatland forests has the largest potential (Ala-Ilomäki et al, 2011), because of a pronounced reduction of suitable logging sites on upland (mineral) soils (Uusitalo and Ala-Ilomäki, 2013). However, more intensive utilization of peatlands is a controversial 25 issue.…”

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“…However, more intensive utilization of peatlands is a controversial 25 issue. Peatlands representing sensitive forest sites are generally characterized by the most difficult forest harvesting conditions (Nugent et al, 2003;Uusitalo and Ala-Ilomäki, 2013;Uusitalo et al, 2015a). Moreover, in addition to the increasing demand of wood harvesting from drained peatlands, there exists a pressure to restore drained peatlands to natural state in order to maintain biodiversity and prevent carbon loss from peatlands (Komulainen et al, 1999;Carroll et al, 2011;Pitkänen et al, 2013).…”

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confidence: 99%

Projected decrease in wintertime bearing capacity on different forest and soil types in Finland under a warming climate

Lehtonen¹,

Venäläinen²,

Kämäräinen³

et al. 2018

Preprint

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Abstract. Trafficability in forest terrain is largely determined by ground-bearing capacity and it is thus one of the most important issues in timber harvesting. In winter, the bearing capacity is mainly determined by soil frost. Particularly on peatland 10 forests bearing capacity is poor under unfrozen conditions. The bearing capacity of forest truck roads is similarly affected by ground frost. Already 20 cm thick layer of frozen soil or 40 cm layer of snow on the ground can carry in Finnish forest conditions heavy machines in forest harvesting. In this work, we studied the impacts of climate change on soil frost conditions, and consequently on ground-bearing capacity of soils from the timber harvesting point of view. The number of days with good wintertime bearing capacity was modelled by using a soil temperature model and wide set of downscaled climate model data 15 until the end of the 21st century. The model was optimized for different forest and soil types. The results show that by the mid21st century, the wintertime bearing season length decreases in Finland most likely by about one month. The decrease in soil frost and wintertime bearing capacity will be more pronounced during the latter half of the century when drained peatlands may virtually lack soil frost in most of winters in southern and western Finland. The projected decrease in the bearing capacity, accompanied with increasing demand for wood harvesting from drained peatlands, induces a clear need for the development 20 of new sustainable and efficient logging practices for drained peatlands.

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The significance of above-ground biomass, moisture content and mechanical properties of peat layer on the bearing capacity of ditched pine bogs

Cited by 32 publications

References 16 publications

Estimating the Rut Depth by UAV Photogrammetry

Estimating the Rut Depth by UAV Photogrammetry

Performance of weather parameters in predicting growing season water table depth variations on drained forested peatlands – a case study from southern Finland

Projected decrease in wintertime bearing capacity on different forest and soil types in Finland under a warming climate

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