• DocumentCode
    576407
  • Title

    Object based data fusion of landform and ancillary data for upscaling soil-landscape mapping in the western Australian pastoral rangelands

  • Author

    Wilson, D. ; Corner, R. ; Schut, T.

  • Author_Institution
    Dept. of Spatial Sci., Curtin Univ., Bentley, WA, Australia
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    7569
  • Lastpage
    7572
  • Abstract
    We have investigated methods to derive landform and vegetation data from a Digital Elevation Model and remote sensing, using classification and segmentation. These data are required to upscale existing regional level landsystem mapping to a higher spatial and thematic resolution (subsystems). In turn the land subsystem data will be used to support rangeland condition mapping in a large area of leasehold rangeland. The derived landform and vegetation classes have been tested against available landsystem mapping derived by conventional methods and have shown promising relationships. These classifications need to be further revised prior to their use in either an object based or probabilistic classifier.
  • Keywords
    data assimilation; digital elevation models; geomorphology; geophysics computing; pattern classification; probability; remote sensing; vegetation; DEM; ancillary data; data classification; data segmentation; digital elevation model; land subsystem data; landform data; object based classifier; object based data fusion; probabilistic classifier; rangeland condition mapping; regional level landsystem mapping; remote sensing; soil landscape map upscaling; vegetation data; western Australian pastoral rangelands; Australia; Digital elevation models; Earth; Remote sensing; Satellites; Soil; Vegetation mapping; Digital Elevation Models; Geographic Information Systems; Land surface; Remote Sensing;
  • 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.2012.6351910
  • Filename
    6351910