Enhanced change detection index for disaster response, recovery assessment and monitoring of buildings and critical facilities: a case study for Muzzaffarabad, Pakistan

<p>The availability of Very High Resolution (VHR) optical sensors and a growing image archive that is frequentlyupdated, allows the use of change detection in post-disaster recovery and monitoring for robust and rapid results.The proposed semi-automated GIS object-based method uses readily available pre-disaster GIS data and addsexisting knowledge into the processing to enhance change detection. It also allows targeting specific types ofchanges pertaining to similar man-made objects such as buildings and critical facilities. The change detectionmethod is based on pre/post normalized index, gradient of intensity, texture and edge similarity filters withinthe object and a set of training data. More emphasis is put on the building edges to capture the structural damagein quantifying change after disaster. Once the change is quantified, based on training data, the method can beused automatically to detect change in order to observe recovery over time in potentially large areas. Analysisover time can also contribute to obtaining a full picture of the recovery and development after disaster, therebygiving managers a better understanding of productive management and recovery practices. The recovery andmonitoring can be analyzed using the index in zones extending from to epicentre of disaster or administrativeboundaries over time.</p>