• DocumentCode
    3353272
  • Title

    Multispectral classification of remote sensing imagery for archaeological land use analysis: Prospective study

  • Author

    Villalon-Turrubiates, Ivan E. ; Llovera-Torres, Maria J.

  • Author_Institution
    Centro Univ. de los Valles, Univ. de Guadalajara, Guadalajara, Mexico
  • fYear
    2010
  • fDate
    25-30 July 2010
  • Firstpage
    323
  • Lastpage
    326
  • Abstract
    Much of human history can be traced through the impacts of human actions upon the environment. The use of remote sensing technology offers the archeologist the opportunity to detect these impacts which are often invisible to the naked eye. The extraction of remote sensing signatures from a particular geographical region allows the generation of geophysical signature maps; this can be achieved using an accurate and recently developed multispectral image classification approach based on pixel statistics for the class description, which is referred to as the Weighted Pixel Statistics method. This paper presents the prospective study of the effectiveness that this approach provides for supervised segmentation and classification of sensed archaeological signatures for land use analysis. The results obtained with this study uses real multispectral scenes obtained with remote sensing techniques (high-resolution synthetic aperture radar) to probe the efficiency of the classification technique.
  • Keywords
    archaeology; geophysical image processing; image classification; image segmentation; realistic images; remote sensing by radar; synthetic aperture radar; archaeological land use analysis; archeologist; class description; classification technique; geographical region; geophysical signature maps; high-resolution synthetic aperture radar; human history; multispectral classification; multispectral image classification approach; real multispectral scenes; remote sensing imagery; remote sensing signatures; remote sensing techniques; remote sensing technology; sensed archaeological signatures; supervised segmentation; weighted pixel statistics method; Classification algorithms; Humans; Image segmentation; Pixel; Remote sensing; Simulation; Synthetic aperture sonar;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
  • Conference_Location
    Honolulu, HI
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4244-9565-8
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2010.5652664
  • Filename
    5652664