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Abstract

Understanding Unplanned Fire Ignition Patterns to Improve Early Fire Detection and Resource Deployment †

1
Fenner School of Environment & Society, Australian National University, Canberra, ACT 2601, Australia
2
School of Engineering, Australian National University, Canberra, ACT 2601, Australia
*
Author to whom correspondence should be addressed.
Presented at the Third International Conference on Fire Behavior and Risk, Sardinia, Italy, 3–6 May 2022.
Environ. Sci. Proc. 2022, 17(1), 30; https://doi.org/10.3390/environsciproc2022017030
Published: 9 August 2022
(This article belongs to the Proceedings of The Third International Conference on Fire Behavior and Risk)

Abstract

:
The early detection of unplanned fires can improve the chances of successful containment and suppression, thus reducing the risk of large and destructive fires. However, detecting fires can be difficult, particularly over large landscapes with variable topography and land use. Information on where and when unplanned fire ignitions are most likely to occur can assist in the strategic deployment of fire-detection resources. The Australian Capital Territory, in temperate southeastern Australia, consists of a large urban centre surrounded by fire-prone forests and grasslands. Conditions expected to influence ignition risk, such as human presence, climate, and fuel type, vary considerably across the region, however climate is the main condition that will vary across the entire region from year to year. Ignitions in the remote and mountainous area to the southwest are likely to be limited by high fuel moisture and fewer ignition sources. While the drier and more populated area in the northeast may support more frequent ignitions. Consequently, ignition occurrence is expected to vary considerably across the region and over time. Here, we present an analysis of unplanned fire ignition patterns across the Australian Capital Territory from 2013 to 2021. Specifically, we ask how annual ignition frequency varies across the region and whether these patterns vary with annual climatic fluctuations. These results are discussed within the context of improving early fire detection and resource deployment.

Author Contributions

Conceptualization, N.W. and M.Y.; methodology, N.W.; formal analysis, N.W.; investigation, N.W.; resources, M.Y.; data curation, N.W.; writing—original draft preparation, N.W.; writing—review and editing, M.Y.; visualization, N.W.; supervision, M.Y.; project administration, N.W. and M.Y.; funding acquisition, M.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partially funded by Optus as part of the ANU-Optus Bushfire Research Centre of Excellence.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Monthly ignition data are available for download from https://zenodo.org/badge/latestdoi/520294094. SILO climate data can be downloaded from https://www.longpaddock.qld.gov.au/silo/.

Conflicts of Interest

The authors declare no conflict of interest.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Wilson, N.; Yebra, M. Understanding Unplanned Fire Ignition Patterns to Improve Early Fire Detection and Resource Deployment. Environ. Sci. Proc. 2022, 17, 30. https://doi.org/10.3390/environsciproc2022017030

AMA Style

Wilson N, Yebra M. Understanding Unplanned Fire Ignition Patterns to Improve Early Fire Detection and Resource Deployment. Environmental Sciences Proceedings. 2022; 17(1):30. https://doi.org/10.3390/environsciproc2022017030

Chicago/Turabian Style

Wilson, Nicholas, and Marta Yebra. 2022. "Understanding Unplanned Fire Ignition Patterns to Improve Early Fire Detection and Resource Deployment" Environmental Sciences Proceedings 17, no. 1: 30. https://doi.org/10.3390/environsciproc2022017030

APA Style

Wilson, N., & Yebra, M. (2022). Understanding Unplanned Fire Ignition Patterns to Improve Early Fire Detection and Resource Deployment. Environmental Sciences Proceedings, 17(1), 30. https://doi.org/10.3390/environsciproc2022017030

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