| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 2.95 MB | Adobe PDF |
Advisor(s)
Abstract(s)
Wildfire susceptibility maps are a well-known tool for optimizing
available means to plan for prevention, early detection, and wildfire
suppression in Portugal, especially regarding the critical fire
season (1 July 30 September). These susceptibility maps typically
disregard seasonal weather conditions on each given year,
being based on predisposing variables that remain constant on
the long-term, such as elevation. We employ logistic regression
for combining wildfire susceptibility with a meteorological index
representing spring conditions (the Seasonal Severity Rating), with
the purpose of predicting, for any given year and ahead of the
critical fire season, which areas will burn. Results show that the
combination of the index with wildfire susceptibility slightly
increases the capability to predict which areas will burn, when
compared with susceptibility alone. Spring meteorological context
was found better suited for predicting if the following summer
wildfire season will be more severe, rather than predicting where
wildfires will effectively occur. The model can be updated yearly
after the critical wildfire season and can be applied to optimize
the allocation of human and material resources regarding the prevention,
early detection and suppression activities, required to
reduce the severity of wildfires in the country.
Description
Keywords
Burnt area model Logistic regression Meteorological wildfire index Seasonal severity rating Wildfire susceptibility
Pedagogical Context
Citation
Bergonse, R., Oliveira, S., Gonçalves, A., Nunes, S., Camara, C., & Zêzere, J. L. (2021). Predicting burnt areas during the summer season in Portugal by combining wildfire susceptibility and spring meteorological conditions. Geomatics, Natural Hazards and Risk, 12(1), 1039-1057. https://doi.org/10.1080/19475705.2021.1909664
Publisher
Taylor & Francis