3D Data Collection and Automated Damage Assessment for Near Real-time Tornado Loss Estimation

Tornadoes cause great hardship and economic loss to U.S. communities each year. The lack of quantitative information associated with real damage states of individual buildings results in inaccurate loss estimates and hampers effective decision making for mitigation, response, and recovery. A near real-time tornado loss estimation tool was developed and tested as part of this work. The GIS-based damage assessment tool employs post-event point cloud data collected by terrestrial scanners and pre-event aerial images. The tool automatically calculates the percentage of roof and wall damage at the individual building scale, which is used as input to empirical or statistical loss estimation methods. An accuracy analysis through a set of controlled experiments indicated that for typical point cloud density (greater than 25 points/m²), the tool results in less than 10% error in detection of pre- and post-event roof/wall surfaces. The GIS-based tool was validated with data sets collected after the 2013 Moore, OK, tornado and produced detailed percentage of damage for buildings, which was not provided by infield inceptions.