• DocumentCode
    2224929
  • Title

    Predicting the adaptability of sudden oak death in China using spatial information technology

  • Author

    Liu, Cheng ; Cao, Chunxiang ; Zhang, Jianlong ; Ma, Aiguo ; Chen, Wei ; Xu, Min ; Sakai, Tetsuro

  • Author_Institution
    State Key Lab. of Remote Sensing Sci., Inst. of Remote Sensing Applic., Beijing, China
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    7256
  • Lastpage
    7259
  • Abstract
    Sudden oak death which is caused by the pathogen phytophthora ramorum has killed thousands of oak trees in Europe and North America in recent decades and also threaten the forests in China. In this study, we choose 4 climate predictor variables to predict the adaptability of sudden oak death in China. First we assign the importance of each variable by using analytic hierarchy process(AHP), and then we build the membership function of each variable by using fuzzy mathematics method. With the climate data of 752 weather stations in China, we interpolate them in GIS to generate the variable layers and compute the final adaptability of sudden oak death by averaging the adaptability in each month of the pathogen´s general reproductive season. The result shows that sudden oak death can be suitable for a wide range in China, most of where are southeastern regions.
  • Keywords
    geographic information systems; vegetation; weather forecasting; China; Europe; North America; analytic hierarchy process; climate data; climate predictor variables; fuzzy mathematics method; geographic information systems; oak trees; pathogen general reproductive season; pathogen phytophthora ramorum; spatial information technology; sudden oak death; weather stations; Adaptation models; Biological system modeling; Computational modeling; Meteorology; Pathogens; Sudden oak death; adaptability; analytic hierarchy process; fuzzy mathematics method; spatial information technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6351987
  • Filename
    6351987