A Damage Prediction Model for Quantity Loss of Skidded Spruce Logs during Ground Base Skidding in North Eastern Turkey

Unver S., ACAR H.

CROATIAN JOURNAL OF FOREST ENGINEERING, vol.30, no.1, pp.59-65, 2009 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 30 Issue: 1
  • Publication Date: 2009
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.59-65
  • Keywords: ground base skidding, log volume loss, damage prediction model
  • Karadeniz Technical University Affiliated: Yes


In Turkey ground base skidding method is frequently used to extract log material. Physical damages occurring on the skidded log during ground based skidding cause quality and quantity loss of the log. This damage is formed by the ground structure, mass of transported logs, friction coefficient and skidding distance. In this study to improve a Damage Prediction Model means to predict the quantity loss that can occur as a result of ground skidding on steep areas. Spruce forests in Macka, Trabzon, Eastern Blacksea, was selected as the study area. The slope of study area ranged between 45% and 80%. In this context, a total of 318 logs were researched. These logs were skidded in 6 harvested areas where skidding is done both in summer and winter. It was determined during research that the types of damage causing quantity loss are breakage and wood wearing out. In the meantime, the quantity loss occurring as a result of breakage and wood wearing out was calculated as volume. A prediction model was developed by taking into consideration friction vector affecting skidded log, friction surface area of the log and skidding distance parameters. The model was developed based on data related to logs skidded in summer and winter. Damage prediction model coefficients were obtained for two production seasons by solving models according to the least squares method. Statistical significance of coefficients was done and damage prediction models were obtained with significant coefficients for summer and winter production seasons. This enabled producers to predict the quantity loss before skidding and to take necessary precautions.