This GIS-based tornado damage assessment model incorporates US national parcel data, the National Weather Service’s (NWS) Damage Assessment Toolkit (DAT) tornado path polygons and damage functions based on the Enhanced Fujita (EF) scale damage indicators used by the National Oceanic and Atmospheric Administration (NOAA) to rate tornadoes according to structural impacts. The model has tested for the three previously mentioned case studies, resulting in 80-95% accuracy when the output damage assessments are compared to those derived manually from high resolution aerial optical imagery and field surveys.
The Enhanced Fujita Scale is a set of wind estimates based on observed damages. It uses 3-second gusts estimated at the point of damage based on a judgment of level of damage. The EF scale tornado path polygons are available through the Damage Assessment Toolkit (DAT) typically 24-72 hours following a tornado.
- The EF scale attributes of the DAT polygons are associated with varying Degrees of Damage for 28 different Damage Indicators.
- The Property Indicators and the Land Use Codes of the National Parcel Dataset are used to assume a Structure Type for the parcels. Additionally, vacant parcels and duplicate parcel points are removed from the analysis.
- The Degrees of Damage for each Damage Indicator are categorized into FEMA Damage Categories, and then applied to the parcel dataset according to each parcel’s Structure Type.
Parcels are intersected with the DAT tornado path polygons in ArcGIS, and assigned a damage category based on the EF scale of the tornado path. These damage counts can be used for preliminary situational awareness and should be replaced by field verified information when it becomes available
Access & Use Information
Public: This dataset is intended for public access and use.
Downloads & Resources
Jones, M. and Pitts, R. An Automated Tornado Damage Assessment Model: Providing Rapid Situational Awareness to the Federal Emergency Management Agency (FEMA). Abstract #326485 presented at 98th American Meteorological Society Annual Meeting, Austin, Texas, 7-11 Jan 2018.