Selection of geographical factors using the random forest analysis method for developing the site index equation of Pinus densiflora stands in Republic of Korea

  • Hee jung Park
  • , Se IK Park
  • , Hyun Soo Kim
  • , Eun Seong Lee
  • , Hyun Jun Kim
  • , Sang Hyun Lee*
  • *Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

Abstract

This study was conducted to establish reasonable forest management plan by developing site index curves about Pinus densiflora stands that is major species growing in Jeolla-do in Republic of Korea. A total of 613 Pinus densiflora plots and 20m × 20m sampling plot was installed for each stand. The altitude height, slope, orientation bearing, soil type, the height and diameter at breast height (1.2 m from the ground) of a dominant tree, and the age of trees were measured. After developing site index curves using Chapman-Richards, Schumacher and Gompertz models, top three geographical factors were added to asymptote and shape parameters. In results, Gompertz model for Pinus densiflora stands was chosen for best model of height and site index model. Also, soil type, parent rock and topography were added into Gompertz model for Pinus densiflora stand as the independent variables, using the random forest analysis method. As result of adding geographical factors to asymptote and shape of Gompertz model for Pinus densiflora stand, the precision of the model has increased with decreasing MSE. As hybrid site index model including geographical factors indicated influence growth of Pinus densiflora, reasonable forest management plan is determined.

Original languageEnglish
Pages (from-to)19-23
Number of pages5
JournalForest Science and Technology
Volume15
Issue number1
DOIs
StatePublished - 2019.01.2

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  2. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • geographical factors
  • Hybrid site index
  • Pinus densiflora
  • site index model
  • the random forest analysis method

Quacquarelli Symonds(QS) Subject Topics

  • Environmental Sciences
  • Agriculture & Forestry

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