Next Article in Journal
Data Assimilation System Applied to Short-Range Forecast System
Previous Article in Journal
Test Bench for Complete Characterization of Evaporative Cooling Pads
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Anticipating Future Extreme Wildfires by Predicting the Probability of Ignition and Escape of Initial Attack in Catalunya †

Fellice Gabrielle Catelo
Marcos Rodrigues
2 and
Aitor Ameztegui
Department of Agriculture and Forest Engineering, University of Lleida, 25003 Lleida, Spain
GEOFOREST Group, Instituto Universitario de Investigación en Ciencias Ambientales de Aragon (IUCA), Department of Geography and Land Management, University of Zaragoza, 50009 Zaragoza, Spain
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), 109;
Published: 30 August 2022
(This article belongs to the Proceedings of The Third International Conference on Fire Behavior and Risk)
In recent years, the EU has implemented several firefighting-related policies to battle and reduce the negative impacts of wildfires. However, the changing environment constantly surprises us with extreme events that cause massive losses for the entire Europe, with the Mediterranean region increasing its vulnerability to these risks. Recently, the wildfire season for the region was observed to have lengthened, and along with the rapid change in fire-weather factors, resulted to extreme wildfire events. As of 2022, total burned area for the EU is recorded to be approx. 792,902 (66% forest) (EFFIS Damage Assessment, 2022). It has long been recognized that the Mediterranean cultural landscape is fire-prone, hence decision-makers see to it that responses and solutions are devoted at mitigating and reducing fire risk. With the advocacy of a paradigm shift to coexist with fire, anticipation of fire incidents is the best approach partnered with comprehensive management. Various studies on wildfires provide geospatial insights and models to foresee fire occurrence, burning extent, success in initial attack, ignition probability, etc.
This study aims to recognize and understand wildfire activity by forecasting the occurrence of extreme wildfire events in the near future. The approach is based on coupling ignition and escape models to climate (C3S) and landcover-change (SEDAC) projections to outline the spatial distribution of wildfires up to 2100. We calibrated a series of binary regression models upon historical records of wildfire ignition in Catalonia (Northeast of Spain) using machine-learning techniques under different land cover change and climate scenarios. Disaster risk reduction will be improved through this prediction by identifying wildfire management zones and prioritization of areas.

Author Contributions

Conceptualization, M.R. and A.A.; Methodology, F.G.C., M.R. and A.A.; software, M.R. and A.A.; Formal analysis, F.G.C. and M.R.; Investigation, F.G.C., M.R. and A.A.; data curation, F.G.C.; Writing—original draft preparation, F.G.C., M.R., and A.A.; writing–reviewing and editing, F.G.C., M.R. and A.A.; visualization, M.R.; supervision, M.R.; project administration, M.R.; funding acquisition, M.R. All authors have read and agreed to the published version of the manuscript.


This work was funded by the Spanish Ministry of Science and Innovation [grant numbers FIREPATHS (PID2020-116556RA-I00). F.G.C was funded with a scholarship by the MSc in European Forestry Programme at the University of Lleida. This work was also funded by project FirEUrisk—DEVELOPING A HOLISTIC, RISK-WISE STRATEGY FOR EUROPEAN WILDFIRE MANAGEMENT, which has 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

Fire records data can be freely downloaded from the website of the Ministry for Ecological Transition and the Demographic Challenge ( Landcover change (human population dynamics) data can also be freely downloaded from the website of Socioeconomic Data and Applications Center (SEDAC) ( Climate prediction data were based on the EU-CORDEX project (available at Earth System Grid Federation; The original weather data is available at the Spanish Meteorological Agency upon request.

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

Catelo, F.G.; Rodrigues, M.; Ameztegui, A. Anticipating Future Extreme Wildfires by Predicting the Probability of Ignition and Escape of Initial Attack in Catalunya. Environ. Sci. Proc. 2022, 17, 109.

AMA Style

Catelo FG, Rodrigues M, Ameztegui A. Anticipating Future Extreme Wildfires by Predicting the Probability of Ignition and Escape of Initial Attack in Catalunya. Environmental Sciences Proceedings. 2022; 17(1):109.

Chicago/Turabian Style

Catelo, Fellice Gabrielle, Marcos Rodrigues, and Aitor Ameztegui. 2022. "Anticipating Future Extreme Wildfires by Predicting the Probability of Ignition and Escape of Initial Attack in Catalunya" Environmental Sciences Proceedings 17, no. 1: 109.

Article Metrics

Back to TopTop