Physical Sciences and Mathematics Commons^™

Impact Of Model Choice In Predicting Urban Forest Storm Damage When Data Is Uncertain, Casey Lambert, Shawn Landry, Michael G. Andreu, Andrew Koeser, Gregory Starr, Christina Staudhammer

School of Geosciences Faculty and Staff Publications

Research that illuminates causes of urban forest storm damage is valuable for planning and management. However, logistical and safety concerns often delay post-storm surveys in urban areas; thus, surveys may include observations with unverified sources of damage. While this uncertainty is often ignored, it can make up a high proportion of the number of damaged trees. The goal of this research was to improve understanding of techniques for modeling storm damage in urban forests. Using urban forest storm damage inventories collected in Florida, post-Hurricane Irma (2017), we tested how different imputation methods, modeling procedures, and damage frequency levels could impact …