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Articles by Harri Lindeman

Category : Research article

article id 10134, category Research article
Matti Sirén, Jari Ala-Ilomäki, Harri Lindeman, Jori Uusitalo, Kalle E.K. Kiilo, Aura Salmivaara, Ari Ryynänen. (2019). Soil disturbance by cut-to-length machinery on mid-grained soils. Silva Fennica vol. 53 no. 2 article id 10134. https://doi.org/10.14214/sf.10134
Keywords: rut formation; soil compaction; sandy soil; silty soil; harvesting damage
Highlights: The number of machine passes, volumetric water content in the mineral soil and the depth of the organic layer were the controlling factors for rut formation; The harvester rut depth was a good predictor of the forwarder rut formation; Changes in the penetration resistance were highest at depths of 20–40 cm.
Abstract | Full text in HTML | Full text in PDF | Author Info

Factors affecting soil disturbance caused by harvester and forwarder were studied on mid-grained soils in Finland. Sample plots were harvested using a one-grip harvester. The harvester operator processed the trees outside the strip roads, and the remaining residues were removed to exclude the covering effect of residues. Thereafter, a loaded forwarder made up to 5 passes over the sample plots. The average rut depth after four machine passes was positively correlated to the volumetric water content at a depth of 0–10 cm in mineral soil, as well as the thickness of the organic layer and the harvester rut depth, and negatively correlated with penetration resistance at depths of both 0–20 cm and 5–40 cm. We present 5 models to predict forwarder rut depth. Four include the cumulative mass driven over a measurement point and combinations of penetration resistance, water content and the depth of organic layer. The fifth model includes harvester rut depth and the cumulative overpassed mass and provided the best fit. Changes in the penetration resistance (PR) were highest at depths of 20–40 cm. Increase in BD and VWC decreased PR, which increased with total overdriven mass. After four to five machine passes PR values started to stabilize.

  • Sirén, Natural Resources Institute Finland (Luke) c/o Aalto University, P.O. Box 15600, FI-00076 Aalto, Finland E-mail: matti.siren@luke.fi (email)
  • Ala-Ilomäki, Natural Resources Institute Finland (Luke) c/o Aalto University, P.O. Box 15600, FI-00076 Aalto, Finland ORCID http://orcid.org/0000-0002-6671-7624 E-mail: jari.ala-ilomaki@luke.fi
  • Lindeman, Natural Resources Institute Finland (Luke), Korkeakoulunkatu 7, FI-33720 Tampere, Finland E-mail: harri.lindeman@luke.fi
  • Uusitalo, Natural Resources Institute Finland (Luke), Korkeakoulunkatu 7, FI-33720 Tampere, Finland ORCID http://orcid.org/0000-0003-3793-1215 E-mail: jori.uusitalo@luke.fi
  • Kiilo, Versowood, Teollisuuskatu 1, FI-11130 Riihimäki, Finland E-mail: kalle.kiilo@versowood.fi
  • Salmivaara, Natural Resources Institute Finland (Luke), P.O. Box 2, FI-00791 Helsinki, Finland E-mail: aura.salmivaara@luke.fi
  • Ryynänen, Natural Resources Institute Finland (Luke), Kaironiementie 15, FI-39700 Parkano, Finland E-mail: ari.ryynanen@luke.fi
article id 10050, category Research article
Jori Uusitalo, Jari Ala-Ilomäki, Harri Lindeman, Jenny Toivio, Matti Siren. (2019). Modelling soil moisture – soil strength relationship of fine-grained upland forest soils. Silva Fennica vol. 53 no. 1 article id 10050. https://doi.org/10.14214/sf.10050
Keywords: cone index; penetration resistance; shear strength; soil bulk density; VWC
Highlights: Penetration resistance (PR) is best predicted with moisture content (MC), bulk density and clay content; In fully saturated silty or clayey soils PR range from 600 to 800 kPa; The models can be linked with mobility models predicting rutting of forest machines.
Abstract | Full text in HTML | Full text in PDF | Author Info

The strength of soil is known to be dependent on water content but the relationship is strongly affected by the type of soil. Accurate moisture content – soil strength models will provide forest managers with the improved ability to reduce soil disturbances and increase annual forest machine utilization rates. The aim of this study was to examine soil strength and how it is connected to the physical properties of fine-grained forest soils; and develop models that could be applied in practical forestry to make predictions on rutting induced by forest machines. Field studies were conducted on two separate forests in Southern Finland. The data consisted of parallel measurements of dry soil bulk density (BD), volumetric water content (VWC) and penetration resistance (PR). The model performance was logical, and the results were in harmony with earlier findings. The accuracy of the models created was tested with independent data. The models may be regarded rather trustworthy, since no significant bias was found. Mean absolute error of roughly 20% was found which may be regarded as acceptable taken into account the character of the penetrometer tool. The models can be linked with mobility models predicting either risks of rutting, compaction or rolling resistance.

  • Uusitalo, Natural Resources Institute Finland (Luke), Production systems, Korkeakoulunkatu 7, FI-33720 Tampere, Finland E-mail: jori.uusitalo@luke.fi (email)
  • Ala-Ilomäki, Natural Resources Institute Finland (Luke), Production systems Maarintie 6, FI-02150 Espoo, Finland E-mail: jari.ala-ilomaki@luke.fi
  • Lindeman, Natural Resources Institute Finland (Luke), Production systems, Korkeakoulunkatu 7, FI-33720 Tampere, Finland E-mail: harri.lindeman@luke.fi
  • Toivio, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: toiviojenny@gmail.com
  • Siren, Natural Resources Institute Finland (Luke), Production systems Maarintie 6, FI-02150 Espoo, Finland E-mail: matti.siren@luke.fi
article id 1687, category Research article
Hannu Hökkä, Jori Uusitalo, Harri Lindeman, Jari Ala-Ilomäki. (2016). Performance of weather parameters in predicting growing season water table depth variations on drained forested peatlands – a case study from southern Finland. Silva Fennica vol. 50 no. 4 article id 1687. https://doi.org/10.14214/sf.1687
Keywords: peatland; precipitation; bearing capacity; evapotranspiration; mixed linear model; water table depth
Highlights: Four-week precipitation and evapotranspiration explain much of drained peatland water table depth variation during a growing season.
Abstract | Full text in HTML | Full text in PDF | Author Info

The 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.

  • Hökkä, Natural Resources Institute Finland (Luke), Management and Production of Renewable Resources, Paavo Havaksen tie 3, FI-90014 Oulun yliopisto, Finland E-mail: hannu.hokka@luke.fi (email)
  • Uusitalo, Natural Resources Institute Finland (Luke), Green Technology, Kaironiementie 15, FI-39700 Parkano, Finland E-mail: jori.uusitalo@luke.fi
  • Lindeman, Natural Resources Institute Finland (Luke), Green Technology, Kaironiementie 15, FI-39700 Parkano, Finland E-mail: harri.lindeman@luke.fi
  • Ala-Ilomäki, Natural Resources Institute Finland (Luke), Green Technology, Jokiniemenkuja 1, FI-01370 Vantaa, Finland E-mail: jari.ala-ilomaki@luke.fi
article id 1568, category Research article
Jouni Siipilehto, Harri Lindeman, Mikko Vastaranta, Xiaowei Yu, Jori Uusitalo. (2016). Reliability of the predicted stand structure for clear-cut stands using optional methods: airborne laser scanning-based methods, smartphone-based forest inventory application Trestima and pre-harvest measurement tool EMO. Silva Fennica vol. 50 no. 3 article id 1568. https://doi.org/10.14214/sf.1568
Keywords: forest inventory; diameter distribution; Weibull; area-based approach; parameter recovery; k-NN estimation
Highlights: An airborne laser scanning grid-based approach for determining stand structure enabled bi- or multimodal predicted distributions that fitted well to the ground-truth harvester data; EMO and Trestima applications needed stand-specific inventory for sample measurements or sample photos, respectively, and at their best, provided superior accuracy for predicting certain stand characteristics.
Abstract | Full text in HTML | Full text in PDF | Author Info

Accurate timber assortment information is required before cuttings to optimize wood allocation and logging activities. Timber assortments can be derived from diameter-height distribution that is most often predicted from the stand characteristics provided by forest inventory. The aim of this study was to assess and compare the accuracy of three different pre-harvest inventory methods in predicting the structure of mainly Scots pine-dominated, clear-cut stands. The investigated methods were an area-based approach (ABA) based on airborne laser scanning data, the smartphone-based forest inventory Trestima app and the more conventional pre-harvest inventory method called EMO. The estimates of diameter-height distributions based on each method were compared to accurate tree taper data measured and registered by the harvester’s measurement systems during the final cut. According to our results, grid-level ABA and Trestima were generally the most accurate methods for predicting diameter-height distribution. ABA provides predictions for systematic 16 m × 16 m grids from which stand-wise characteristics are aggregated. In order to enable multimodal stand-wise distributions, distributions must be predicted for each grid cell and then aggregated for the stand level, instead of predicting a distribution from the aggregated stand-level characteristics. Trestima required a sufficient sample for reliable results. EMO provided accurate results for the dominating Scots pine but, it could not capture minor admixtures. ABA seemed rather trustworthy in predicting stand characteristics and diameter distribution of standing trees prior to harvesting. Therefore, if up-to-date ABA information is available, only limited benefits can be obtained from stand-specific inventory using Trestima or EMO in mature pine or spruce-dominated forests.

  • Siipilehto, Natural Research Institute Finland (Luke), Management and Production of Renewable Resources, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: jouni.siipilehto@luke.fi (email)
  • Lindeman,  Natural Research Institute Finland, Green Technology, Kaironiementie 15, 39700 Parkano E-mail: harri.lindeman@luke.fi
  • Vastaranta, University of Helsinki, Department of Forest Sciences, P.O. Box 62 (Viikinkaari 11), FI-00014 University of Helsinki E-mail: mikko.vastaranta@helsinki.fi
  • Yu, Finnish Geospatial Research Institute (FGI), Department of Remote Sensing and Photogrammetry, National Land Survey of Finland, P.O. Box 15 (Geodeetinrinne 2), FI-02431, Masala, Finland E-mail: xiaowei.yu@maanmittauslaitos.fi
  • Uusitalo,  Natural Research Institute Finland, Green Technology, Kaironiementie 15, 39700 Parkano E-mail: jori.uusitalo@luke.fi

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