• DocumentCode
    2922739
  • Title

    Study on Measurement Model for Forest Risk Assessment in Beijing

  • Author

    Ying, Zhang ; Jian-wei, Ji ; Ai-jun, Yi ; Ji, Lu

  • Author_Institution
    Sch. of Econ. & Manage., Beijing Forestry Univ., Beijing, China
  • fYear
    2011
  • fDate
    19-20 Feb. 2011
  • Firstpage
    1750
  • Lastpage
    1755
  • Abstract
    It has an important significance to promote the Beijing forestry development and strengthen forest resources management for study on Beijing forest measurement model of risk assessment. This paper has studied on forest measurement model of risk assessment in Beijing used probability regression method. The results show that: Beijing forest fires and forestry production value has a certain relationship, also it has a certain relationship between forest diseases, pests and rodents and forest construction investment, and both statistical tests are significant, which indicated that the regression models are qualified. The study suggests that when carrying out forestry production, forest fire prevention should be enhanced and the forest capital investment should be strengthened to prevent the forest diseases and pests and rodents occurred.
  • Keywords
    fires; forestry; investment; probability; regression analysis; risk management; Beijing forestry development; forest capital investment; forest construction investment; forest diseases; forest fires; forest measurement model; forest resource management; forestry production value; pests; probability regression method; risk assessment; rodents; Biological system modeling; Cities and towns; Diseases; Fires; Forestry; Insects; Rodents; Beijing; forest; management; measurement model; probability regression; risk assessment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2011 International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-61284-278-3
  • Electronic_ISBN
    978-0-7695-4350-5
  • Type

    conf

  • DOI
    10.1109/CDCIEM.2011.494
  • Filename
    5748156