Mobile Tree Failure Prediction for Storm Preparation & Response (C1-R8-08)

A systematic, nationwide survey and review to identify existing inventory/storm response data sets and storm preparation capacity. The results of the review will be used to create a baseline data set for a tree failure prediction model. The modei would serve as the backbone of a mobile data collection and online risk mapping application included as part of an updated and comprehensive stmm preparation and response toolkit.

Urban forest managers are limited in their ability to predict tree failure during storms. If funded, we would create an openly available data collection and GIS mapping mobile application to help professionals quantify tree risk in the urban forest. This process would begin with a systematic, nation-wide survey of wind-related tree failure data. Predictive models built from the data would then be incorporated into a tree-failure prediction tool, offering a direct application of the research conducted. Model building is a continual process which requires additional data to gauge and increase predictive success. To encourage pre-storm data collection, the tree-failure prediction tool will provide users with multiple outputs (i.e. risk maps, i-Tree Eco estimates, and i-Tree Storm inputs.) that can maximize the return on investment in an inventory. In the wake of a storm, the data could be easily updated by municipal staff; members of the USDA Forest Service's Urban Forest Strike Team or community volunteers. Tree failure data derived from these applications will be made openly available to all researchers and professionals through the International Tree Failure Database, providing the standardized data needed to enhance our understanding of wind-related tree failure. Finally, a "Best Management Practices" guidebook that addresses storm preparation and response will be developed. The guidebook will help urban forest managers utilize the proposed application, as well as other tools currently available, to their fullest potential as part of an integrated storm preparation and response strategy.

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