Tornado Risk and Impact Analysis Using Tornado Risk and Impact Analysis Using Dasymetric ModelingDasymetric Modeling

John D. Crabtree, Ph.D.Department of Computer Science and

Information SystemsUniversity of North Alabama

AbstractAbstract

Accurate information is critical to planners and first responders. Inaccuracies and inconsistencies can have a deleterious impact on disaster planning, preparedness, emergency response, disaster recovery and risk mitigation. This presentation demonstrates a technique that can be used to improve the quality of any population data set and its application to the analysis of eight years of tornado data from the National Weather Service. Population maps created from any data source (e.g., census tract, census block, tax assessment, etc.) can be intelligently disaggregated to create more accurate population distributions that can then be analyzed through the intersection of actual or projected risk polygons.

Problem StatementProblem Statement

• Accurate disaster maps are important– Facilitate emergency response efforts– Aid in disaster recovery– Improve risk mitigation and management

• Population data are critical in map creation• Common data analysis methods are poor

– FEMA HAZUS-MH algorithm excludes the entire census unit if the centroid of the unit is not within the risk area (e.g., tornado warning polygon)

Dasymetric MappingDasymetric Mapping

• Dasymetric: Russian transliteration of the Greek terms for density and measuring (dazimetricheskiy) translated into English

• Displays surface data by partitioning space into zones that represent the underlying surface variation

• Often used to disaggregate population data• Uses ancillary data set

41,635

94,298 62,138

Hot Spot AnalysisHot Spot Analysis

Current and Future ResearchCurrent and Future Research

• Statistical comparison of accuracy of density distribution– HAZUS-HM– Census Tract– Dasymetric– Census Block

• Compare dasymetric census block to property tax assessment data

• Compare various dasymetric algorithms

AcknowledgementsAcknowledgements

• Cameron Martin, Geography Student, University of North Alabama – Conference Poster Display

• Jeremy Mennis, Associate Professor, Temple University

• Torrin Hultgren, Graduate Student, University of Colorado