• DocumentCode
    1563960
  • Title

    Expert Systems for Earthquake Damage Assessment

  • Author

    Cheema, Umair

  • Author_Institution
    Nat. Univ. of Comput. & Emerging Sci., Islamabad
  • fYear
    2006
  • Firstpage
    29
  • Lastpage
    32
  • Abstract
    Earthquake is a calamity that can cause colossal damage to buildings, infrastructure and environment consequently leading to heavy casualties. It is therefore imperative for disaster relief agencies and civil protection bodies to assess the damage for planning purposes. Satellite remote sensing and geographic information systems can help prepare initial damage assessment maps. This paper examines the preparation of damage assessment maps using decision tree based expert systems. The inductive machine learning based decision tree classification has correctly identified 61% of the severely damaged buildings and hence is a viable option for preparing damage assessment maps
  • Keywords
    earthquakes; expert systems; geographic information systems; learning (artificial intelligence); remote sensing; damage assessment maps; decision tree; earthquake damage assessment; expert systems; geographic information systems; inductive machine learning; satellite remote sensing; Decision trees; Detection algorithms; Disaster management; Earthquakes; Expert systems; Geographic Information Systems; Machine learning; Protection; Remote sensing; Satellites;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Space Technologies, 2006 International Conference on
  • Conference_Location
    Islamabad
  • Print_ISBN
    1-4244-0515-7
  • Electronic_ISBN
    1-4244-0515-7
  • Type

    conf

  • DOI
    10.1109/ICAST.2006.313792
  • Filename
    4106403