Date of Award


Document Type

Campus Access Thesis



First Advisor

Sarah E. Battersby


Remote sensing imagery plays a crucial role in emergency management when hazard and disaster events happen. Rapid damage assessment is time-critical to distribute accessible response resources and accelerate relief efforts. Currently there are many researchers focusing on post-disaster damage assessment studies, most of which are based on fine-resolution remote sensing imagery. In view of the fact that finer resolution remote sensing imagery requires longer time to collect, transmit and process, this study introduces a new project involving cognitive assessment of post-disaster imagery requirements to determine the coarsest spatial resolution for common post-disaster building damage assessment tasks. To determine this coarsest level of resolution that is acceptable for identifying building damage, an online survey was conducted. This survey was distributed to three groups of participants (novice imagery interpreters, advanced hazards practitioners, and expert imagery analysts) that were selected to be reflective of the type of users that would encounter the imagery in a post-disaster situation. Analysis of the survey data indicates that 1.5m is the coarsest spatial resolution that can be used for successful post-disaster building damage assessment. It was also noted that imagery at a spatial resolution finer than 1m did not provide any significant increase in accuracy of the damage assessment. This study combines remote sensing theory with cognitive science to identify the coarsest spatial resolution for post-disaster building damage assessment and contributes to accurate interpretation and time-saving purposes during rescue and recovery from the events.


© 2010, Jiayu Wang