Using Remote Sensing and Progress Detection to Measure and Monitor Long Term Disaster Recovery in Post Katrina New Orleans, LA

Remote sensing has frequently been used for emergency response and damage assessment after natural disasters.  However, techniques for analysis of long term disaster recovery using remote sensing have not been widely explored.  With increased availability and lower costs, remote sensing offers an objective perspective, systematic and repeatable analysis, and provides a substitute to multiple site visits.  In addition, remote sensing allows access to large geographical areas and areas where ground access may be disrupted, restricted or denied.  This research will focus on the long term recovery of the impacts of Hurricane Katrina on New Orleans, LA and investigate change detection techniques to adequately measure and monitor long term disaster recovery indicators.  Change detection will be used with multi-temporal aerial images to quantitatively measure the progress of recovery.  This work seeks to examine the use of change detection techniques and high resolution aerial images to identify key disaster recovery indicators and provide a spatiotemporal basis for detecting progress.  Images will be classified to automatically identify disaster recovery indicators, and determine which particular indicators are more likely to have a strong impact on recovery assessment.  By tracking the trajectory of 24 individual indicators, the status of recovery progress can be determined for a given location at a given time.