Identifying the danger of fire is important for both wildfire prevention and protection. It can be useful for improving automatic fire detection systems, but also for many other fire-fighting activities that happen before the actual wildfire. The Croatian wildfire risk index is related to estimation of wildfire ignition danger and propagation danger. It is calculated on a micro-location level; therefore, it is a site-specific wildfire risk index. During its development, we have studied the possible influence of various parameters on risk index value using the correlation analysis with past wildfires in Split-Dalmatia County. Finally, two categories of parameters have been chosen:
- Static parameters: vegetation (fuel fire sensitivity), terrain configuration (elevation, slope, aspect) and anthropogenic parameters (settlements, roads, transmission lines);
- Dynamic parameters: wind speed and direction (correlated with slope and aspect) and Canadian Forest Fire Weather Index (FWI). Dynamic parameters are provided by the Croatian Meteorological Service once a day with 24 h forecast by ALADIN model in a 3 h time scale. The relative influence of specific parameter to overall risk index value were optimized by genetic algorithms.
In its present version, it is integrated with the Croatian online wildfire intelligent monitoring and surveillance system (OIV Fire Detect AI) installed in Croatian Dalmatian counties and has been used by Croatian firefighters in everyday practice since 2016.
Currently, we are working on its further improvement through the H2020 FirEUrisk project, particularly in parts dedicated to propagation danger and wildfire vulnerability, but also in more accurate determination of parameters’ influence and new user-friendly visualization.
In our research, we will describe in more detail how the Croatian wildfire risk index is calculated and used, including its statistical evaluation, but also how it will be improved through FirEUrisk project.
Author Contributions
Conceptualization, D.S. and M.B. and L.Š.; methodology, D.S. and L.Š.; software, M.B.; validation, D.K., D.B.-Š.; investigation, D.K.; resources, L.Š.; data curation, D.B.-Š.; writing—original draft preparation, D.S. and M.B.; writing—review and editing, D.S. and M.B. All authors have read and agreed to the published version of the manuscript.
Funding
This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101003890.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
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