• DocumentCode
    3444230
  • Title

    Detecting responses of masson pine to acid rain based on different soil conditions

  • Author

    Jiaxin Jin ; Hong Jiang ; Xiuying Zhang ; Pengwei Xu ; Liya Fan ; Ying Wang

  • Author_Institution
    Int. Inst. for Earth Syst. Sci., Nanjing Univ., Nanjing, China
  • fYear
    2013
  • fDate
    20-22 June 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    To detect responses of masson pine to the acid rain based on different soil conditions, monthly average pH and NDVI were obtained from precipitation acidity and GIMMS/NDVI data from 1992 to 2006 in China based on both acidity levels and soil critical load of acid deposition, then used to analyze inter-annual variation by the improved sinusoidal fitting and linear regression analysis. Our results showed that at severe and slight acidity level, the moderate soil condition was most beneficial to the growth of masson pine, followed by the well soil condition. At moderate acidity level, the worse soil condition was more unfavorable to the growth of masson pine. The multi-year monthly average NDVI showed neither significant difference between poor and moderate soil condition nor between moderate and well soil condition, while the significant difference of the NDVI value between poor and well soil condition in the whole year except in summer.
  • Keywords
    air pollution; atmospheric precipitation; pH; soil; soil pollution; vegetation; AD 1992 to 2006; China; GIMMS-NDVI data; acid deposition; acid rain; acidity levels; linear regression analysis; masson pine; monthly average pH; multiyear monthly average NDVI; precipitation acidity; soil conditions; soil critical load; Ecosystems; Market research; Rain; Remote sensing; Soil; Stress; Vegetation mapping; Acid rain; Masson pine; NDVI; Soil critical load of acid deposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics (GEOINFORMATICS), 2013 21st International Conference on
  • Conference_Location
    Kaifeng
  • ISSN
    2161-024X
  • Type

    conf

  • DOI
    10.1109/Geoinformatics.2013.6626025
  • Filename
    6626025