BBAuthors: Vetrivel, A.; Advisor: -; Participants: - (2016)
Automated damage assessment based on satellite imagery is crucial for initiating fast response actions. Several methods based on supervised learning approaches have been reported as effective for automated mapping of damages using remote sensing images. However, adopting these methods for practical use is still challenging, as they typically demand large amounts of training samples to build a supervised classifier, which are usually not readily available. With the advancement in technologies local and detailed damage assessment for individual buildings is being made available, for example through analysis of images captured by unmanned aerial vehicles, monitoring systems installed in ...