Articles | Volume 22, issue 3
Nat. Hazards Earth Syst. Sci., 22, 1055–1072, 2022
https://doi.org/10.5194/nhess-22-1055-2022
Nat. Hazards Earth Syst. Sci., 22, 1055–1072, 2022
https://doi.org/10.5194/nhess-22-1055-2022
Research article
30 Mar 2022
Research article | 30 Mar 2022

Regional county-level housing inventory predictions and the effects on hurricane risk

Caroline J. Williams et al.

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Cited articles

Aburas, M. M., Ahamad, M. S. S., and Omar, N. Q.: Spatio-temporal simulation and prediction of land-use change using conventional and machine learning models: a review, Environ. Monit. Assess., 191, 205, https://doi.org/10.1007/s10661-019-7330-6, 2019. 
Ali, G. G., El-Adaway, I. H., and Dagli, C.: A System Dynamics Approach for Study of Population Growth and The Residential Housing Market in the US, Proced. Comput. Sci., 168, 154–160, https://doi.org/10.1016/j.procs.2020.02.281, 2020. 
Ashley, W. S. and Strader, S. M.: Recipe for Disaster: How the Dynamic Ingredients of Risk and Exposure Are Changing the Tornado Disaster Landscape, B. Am. Meteor. Soc., 97, 767–786, https://doi.org/10.1175/BAMS-D-15-00150.1, 2016. 
Ashley, W. S., Strader, S., Rosencrants, T., and Krmenec, A. J.: Spatiotemporal Changes in Tornado Hazard Exposure: The Case of the Expanding Bull's-Eye Effect in Chicago, Illinois, Weather Clim. Soc., 6, 175–193, https://doi.org/10.1175/WCAS-D-13-00047.1, 2014. 
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A neural network model based on publicly available data was developed to forecast the number of housing units for each of 1000 counties in the southeastern United States in each of the next 20 years. The estimated number of housing units is almost always (97 % of the time) less than 1 percentage point different than the observed number, which are predictive errors acceptable for most practical purposes. The housing unit projections can help quantify changes in future expected hurricane impacts.
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