• DocumentCode
    513416
  • Title

    Estimation of accumulation area ratio of a glacier from multitemporal satellite images using spectral unmixing

  • Author

    Chan, Jonathan Cheung-Wai ; Van Ophem, Jeremy ; Huybrechts, Philippe

  • Author_Institution
    Dept. of Geogr., Vrije Univ. Brussel, Brussels, Belgium
  • Volume
    2
  • fYear
    2009
  • fDate
    12-17 July 2009
  • Abstract
    The snowline altitude (SLA) and the accumulation area ratio (AAR) of the Morteratsch glacier, Switzerland are derived using Landsat images over a period of 20 year. To draw the SLA, multitemporal Landsat images are first calibrated to surface reflectance using 6S [1]. A linear spectral unmixing algorithm is applied with accumulation and ablation end-members. Transects best representing the morphology of the glacier are drawn and the SLA is defined using the shifts between the end-member profiles of snow and ice. The results of two mass balance characteristics, SLA and AAR, show that the Morteratsch glacier has changed substantially during the period between 1985 and 2005. The average SLA of the glacier has risen by 131 m and the AAR decreased from 66.2 % to 52.5 % during this period. Comparatively, the eastern part of the Morteratsch glacier has a smaller increase (94 m) in the altitude of the snowline, as compared to that of the western part (183 m).
  • Keywords
    glaciology; ice; remote sensing; snow; AD 1985 to 2005; Morteratsch glacier; Switzerland; accumulation area ratio estimation; glacier morphology; ice profiles; linear spectral unmixing algorithm; multitemporal Landsat images; snow profiles; snowline altitude; surface reflectance; Geography; Ice; Monitoring; Reflectivity; Remote sensing; Satellites; Snow; Spectral analysis; Surface morphology; Time measurement; Glacier; accumulation area ratio; snowline; spectral unmixing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009
  • Conference_Location
    Cape Town
  • Print_ISBN
    978-1-4244-3394-0
  • Electronic_ISBN
    978-1-4244-3395-7
  • Type

    conf

  • DOI
    10.1109/IGARSS.2009.5418157
  • Filename
    5418157