• DocumentCode
    142717
  • Title

    Large-scale detection of vegetation dynamics using MODIS images and BFAST: A case study in Quebec, Canada

  • Author

    Xiuqin Fang ; Qiuan Zhu ; Liliang Ren ; Hanwei Xu ; Huai Chen ; Changhui Peng

  • Author_Institution
    Sch. of Earth Sci. & Eng., Hohai Univ., Nanjing, China
  • fYear
    2014
  • fDate
    13-18 July 2014
  • Firstpage
    768
  • Lastpage
    771
  • Abstract
    BFAST (Breaks For Additive Seasonal and Trend) method and MODIS NDVI data were used to detect vegetation dynamics in Quebec during the period of 2000-2012. The Permanent Sample Plots (PSP) data were used to assess the detection method. The results demonstrated that 25.68% of the study area experienced NDVI trend changes during the research period. The detected timing of the biggest changes showed obviously that the areas with the biggest change in 2009 and 2002 were the top two with area percentages of 29.12% and 17.41%, respectively. The results suggested that abrupt vegetation greening occurred especially in 2009 with 58.33% of the overall abrupt greening. The abrupt vegetation browning occurred especially in 2002 with 28.22% of the overall abrupt browning. “Total cut” and “total burning” could be monitored easily using BFAST approach while “insect outbreak” and “plantation” could not be detected satisfyingly.
  • Keywords
    remote sensing; vegetation mapping; AD 2000 to 2012; AD 2009 to 2002; BFAST; BFAST approach; Canada; MODIS NDVI data; MODIS images; NDVI trend changes; Quebec; breaks-for-additive-seasonal-and-trend method; detection method; insect outbreak; large-scale vegetation dynamics detection; permanent sample plots data; plantation; vegetation greening; MODIS; Market research; Remote sensing; Satellites; Time series analysis; Timing; Vegetation mapping; BFAST; MODIS NDVI; vegetation dynamics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
  • Conference_Location
    Quebec City, QC
  • Type

    conf

  • DOI
    10.1109/IGARSS.2014.6946537
  • Filename
    6946537