Open Access. Powered by Scholars. Published by Universities.®

Medicine and Health Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

2013

Wildfire

Articles 1 - 2 of 2

Full-Text Articles in Medicine and Health Sciences

Defining The Importance Of Mental Preparedness For Risk Communication And Residents Well-Prepared For Wildfire, Christine Eriksen, Timothy Prior Jan 2013

Defining The Importance Of Mental Preparedness For Risk Communication And Residents Well-Prepared For Wildfire, Christine Eriksen, Timothy Prior

Faculty of Science, Medicine and Health - Papers: part A

Building on a recognised information-to-action gap in wildfire risk communication, this paper examines what being physically and mentally 'well prepared' actually means to wildfire agency staff and volunteers in charge of disseminating risk information. Using the results of an open-ended survey conducted in southeast Australia, we examine how a set of preparedness messages is interpreted. The paper demonstrates that the concept of wildfire preparedness is ambiguous, and that being 'well prepared' is a complex mix of practical and mental preparedness measures. Many of the individual interpretations of preparedness messages are found to not align with the official outlined intent. In …


The Spatial Domain Of Wildfire Risk And Response In The Wildland Urban Interface In Sydney, Australia, O F. Price, R A. Bradstock Jan 2013

The Spatial Domain Of Wildfire Risk And Response In The Wildland Urban Interface In Sydney, Australia, O F. Price, R A. Bradstock

Faculty of Science, Medicine and Health - Papers: part A

In order to quantify the risks from fire at the wildland urban interface (WUI), it is important to understand where fires occur and their likelihood of spreading to the WUI. For each of the 999 fires in the Sydney region we calculated the distance between the ignition and the WUI, the fire's weather and wind direction and whether it spread to the WUI. The likelihood of burning the WUI was analysed using binomial regression. Weather and distance interacted such that under mild weather conditions, the model predicted only a 5% chance that a fire starting >2.5 km from the interface …