# P. Karpacheva Irina, PhD.

### Simulation Studies on Line Intersect Sampling of Residues Left After Cut-to-Length Logging

volume: 41, issue: 1

Upon carrying out logging, residues remain in the cutting area. Logging residues are an additional source of wood raw material for the production of fuel chips to be used in bioenergetics. In order to plan the logging residues collection and processing technology, it is necessary to gather information on the amount of this type of waste and its distribution within the cutting area.

The article deals with the line intersect (LIS) method.

The aim of this article was to assess the accuracy of the LIS method for quantifying logging residues after cut-to-length logging (CTL), uniformly distributed within the technology traffic lanes (strips) of width b on the cutting area of arbitrary shape S.

The studies were conducted using computer simulations. In the models, logging residues are represented as clusters in the form of circles. The laws of distribution of the radius of the clusters and their position in the plot were determined by field measurements.

In the simulations, clusters uniformly distributed along the X-axis and stripes on the Y-axis were considered. The samples of lines were the set of lines of different length and mutually perpendicular and parallel to the coordinate axes X, Y.

In the simulations, four types of stripes were considered with a different angle to the Y-axis. Type 1 – angle = 0°, type 2 – angle = 15°, type 3 angle = 30°, type 4 – angle = 45°.

It was determined through simulation that the estimated mean radius of the clusters is greater by 24% than the true mean radius.

The LIS method formula is appropriate for estimating the amount of forest residues after CTL logging provided the true mean radius is taken. According to the results of simulation experiments, it was found that the results are in good agreement with the theoretical formulas if the location of the sample lines is mutually perpendicular and parallel to the coordinate axes X, Y of the area. Differences remain within the limits of 20% error

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Web of Science Impact factor (2019): 2.500
Five-years impact factor: 2.077

Quartile: Q1 - Forestry

Subject area

Agricultural and Biological Sciences

Category/Quartile

Forestry/Q1