• DocumentCode
    931443
  • Title

    Expert Systems for Earthquake Damage Assessment

  • Author

    Cheema, Umair

  • Author_Institution
    Nat. Univ. of Comput. & Emerging Sci., Islamabad
  • Volume
    22
  • Issue
    9
  • fYear
    2007
  • Firstpage
    6
  • Lastpage
    10
  • Abstract
    An 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 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
    decision trees; disasters; earthquakes; expert systems; geographic information systems; learning (artificial intelligence); remote sensing; civil protection bodies; decision tree-based expert systems; disaster relief agency; earthquake damage assessment map; geographic information systems; inductive machine learning-based decision tree classification; satellite remote sensing; Decision trees; Detection algorithms; Disaster management; Earthquakes; Expert systems; Geographic Information Systems; Humans; Protection; Remote sensing; Satellites;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    0885-8985
  • Type

    jour

  • DOI
    10.1109/MAES.2007.4350252
  • Filename
    4350252