After a volcanic eruption, assessing building damage quickly is important for responding to and recovering from the disaster. Traditional damage assessment methods such as ground surveys can be time-consuming and resource-intensive, hindering rapid response and recovery efforts. To overcome this, we have developed an automated approach for tephra fall building damage assessment. Our approach uses drone-acquired optical images and deep learning to rapidly generate building damage data.