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Abstract Exposure has amplified rapidly over the past half century and is one of the primary drivers of increases in disaster frequency and consequences. Previous research on exposure change detection has proven limited since the geographic units of aggregation for decennial censuses, the sole measure of accurate historical population and housing counts, vary from one census to the next. To address this shortcoming, this research produces a set of gridded population and housing data for the Chicago, Illinois, region to evaluate the concept of the “expanding bull’s-eye effect.” This effect argues that “targets”—people and their built environments—of geophysical hazards are enlarging as populations grow and spread. A collection of observationally derived synthetic violent tornadoes are transposed across fine-geographic-scale population and housing unit grids at different time stamps to appraise the concept. Results reveal that intensifying and expanding development is placing more people and their possessions in the potential path of tornadoes, increasing the likelihood of tornado disasters. The research demonstrates how different development morphologies lead to varying exposure rates that contribute to the unevenness of potential weather-related disasters across the landscape. In addition, the investigation appraises the viability of using a gridded framework for assessing changes in census-derived exposure data. The creation of uniformly sized grid data on a scale smaller than counties, municipalities, and conventional census geographic units addresses two of the most critical problems assessing historical changes in disaster frequencies and magnitudes—highly variable spatial units of exposure data and the mismatch between spatial scales of population/housing data and hazards.
Ashley et al. (Wed,) studied this question.