• DocumentCode
    3634497
  • Title

    Geological Units Classification of Multispectral Images by Using Support Vector Machines

  • Author

    Miloš Kovacevic;Branislav Bajat;Branislav Trivic;Radmila Pavlovic

  • Author_Institution
    Fac. of Civil Eng., Univ. of Belgrade, Belgrade, Serbia
  • fYear
    2009
  • Firstpage
    267
  • Lastpage
    272
  • Abstract
    Quantitative techniques for spatial prediction and classification in geological survey are developing rapidly. The recent applications of machine learning techniques confirm possibilities of their application in this field of research. The paper introduces Support Vector Machines, a method derived from recent achievements in the statistical learning theory, in classification of geological units based on the source of the Landsat multispectral images. The initial experiments suggest the usefulness of the proposed classification approach.
  • Keywords
    "Geology","Multispectral imaging","Support vector machines","Support vector machine classification","Remote sensing","Satellites","Learning systems","Electronic mail","Machine learning","Statistical learning"
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networking and Collaborative Systems, 2009. INCOS ´09. International Conference on
  • Print_ISBN
    978-1-4244-5165-4
  • Type

    conf

  • DOI
    10.1109/INCOS.2009.44
  • Filename
    5368959