Determining the likelihood of asset destruction during wildfires: Modelling house destruction with fire simulator outputs and local-scale landscape properties

Abstract

Preventing the loss of human lives and the destruction of houses is a focus of land management in fire prone environments. An understanding of the location and nature of risks to assets is important to plan mitigation activities. House destruction during wildfires has been found to be a function of landscape properties, including fuel proximity, topography and proximity to other houses. Additionally, conditions during wildfires are important, with houses likely to be destroyed when flames are intense. We propose an approach to predict destruction that considers both landscape attributes and fire conditions by using historic fires to train a destruction function. This was achieved by linking ..