Expert Systems for Earthquake Damage Assessment

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.