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Modeling the Propagation of Forest Insect Infestation Using Machine Learning Techniques

  • Mileva Samardžić-PetrovićEmail author
  • Suzana Dragićević
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9157)

Abstract

Infestations caused by the mountain pine beetle (MPB) can be seen as complex spatio-temporal process with severe ecological impacts on the forest environment. In order to manage and prevent the insect infestation and reduce significant forest loss it is necessary to improve knowledge about the infestation process. The main objective of this research study is to design and implement a model based on decision trees (DT) mashie learning (ML) technique to forecast the spatial propagation of MPB infestation. The study is implemented in the Bulkley-Nechako region of British Columbia, Canada using data sets for the three time points 2004, 2008 and 2012. The results indicate that the derived DT can accurately characterize the relationships between the considered factors and MPB propagation. The developed DT method can be used to estimate future spread patterns of MPB infestations.

Keywords

Machine learning Decision tree method Geographic information system Spatial modeling Mountain pine beetle Insect infestation 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Mileva Samardžić-Petrović
    • 1
    Email author
  • Suzana Dragićević
    • 1
  1. 1.Spatial Analysis and Modeling Laboratory, Department of GeographySimon Fraser UniversityBurnabyCanada

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