• DocumentCode
    2225094
  • Title

    Detection of forest disturbance in the Greater Hinggan Mountain of China based on Landsat time-series data

  • Author

    Chen, Wei ; Sakai, Tetsuro ; Cao, Chunxiang ; Moriya, Kazuyuki ; Koyama, Lina

  • Author_Institution
    Dept. of Social Inf., Kyoto Univ., Kyoto, Japan
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    7232
  • Lastpage
    7235
  • Abstract
    The detection of forest disturbance, as a key process in monitoring terrestrial ecosystems, has been regarded as an effective approach for indicating the effect of various factors on biological communities. With the advancement of remote sensing technology in large-scale ecology research, we had developed a proposal to detect the change of forest community disturbance in the Greater Hinggan Mountain area of Northeast China using time-series remote sensing data. Firstly, four scenes of Landsat images from four periods of 1990-era, 2000-era, 2005-era and 2010-era were selected and pre-processed. Then, based on the Tasseled Cap transformation, the disturbance index (DI) was calculated and finally the resulting disturbance situations from different periods were analyzed. These results provided significant information on the monitoring and management of local forest.
  • Keywords
    ecology; forestry; geophysical image processing; time series; vegetation mapping; AD 1990 to 2010; Greater Hinggan Mountain; Landsat images; Landsat time-series data; Northeast China; Tasseled Cap transformation; biological communities; disturbance index; forest disturbance detection; large-scale ecology research; local forest management; local forest monitoring; remote sensing technology; terrestrial ecosystem monitoring; time-series remote sensing data; Brightness; Earth; Ecosystems; Indexes; Monitoring; Remote sensing; Satellites; Disturbance index; Forest disturbance; Landsat images; Remote Sensing; Time-series;
  • 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.2012.6351993
  • Filename
    6351993