Country-Level Modeling of Forest Fires in Austria and the Czech Republic: Insights from Open-Source Data
Slobodan Milanović (),
Zoran Trailović (),
Sladjan D. Milanović,
Eduard Hochbichler,
Thomas Kirisits,
Markus Immitzer,
Petr Čermák,
Radek Pokorný,
Libor Jankovský and
Abolfazl Jaafari
Additional contact information
Slobodan Milanović: Department of Forest Protection and Wildlife Management, Faculty of Forestry and Wood Technology, Mendel University in Brno, 613 00 Brno, Czech Republic
Zoran Trailović: Department of Forest and Soil Sciences, Institute of Silviculture, University of Natural Resources and Life Sciences, Vienna (BOKU), 1190 Vienna, Austria
Sladjan D. Milanović: Department for Biomechanics, Biomedical Engineering and Physics of Complex Systems, Institute for Medical Research, University of Belgrade, 11000 Belgrade, Serbia
Eduard Hochbichler: Department of Forest and Soil Sciences, Institute of Silviculture, University of Natural Resources and Life Sciences, Vienna (BOKU), 1190 Vienna, Austria
Thomas Kirisits: Department of Forest and Soil Sciences, Institute of Forest Entomology, Forest Pathology and Forest Protection (IFFF), University of Natural Resources and Life Sciences, Vienna (BOKU), 1190 Vienna, Austria
Markus Immitzer: Department of Landscape, Spatial and Infrastructure Sciences, Institute of Geomatics, University of Natural Resources and Life Sciences, Vienna (BOKU), 1190 Vienna, Austria
Petr Čermák: Department of Forest Protection and Wildlife Management, Faculty of Forestry and Wood Technology, Mendel University in Brno, 613 00 Brno, Czech Republic
Radek Pokorný: Department of Silviculture, Faculty of Forestry and Wood Technology, Mendel University in Brno, 613 00 Brno, Czech Republic
Libor Jankovský: Department of Forest Protection and Wildlife Management, Faculty of Forestry and Wood Technology, Mendel University in Brno, 613 00 Brno, Czech Republic
Abolfazl Jaafari: Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran 1496793612, Iran
Sustainability, 2023, vol. 15, issue 6, 1-20
Abstract:
Forest fires are becoming a serious concern in Central European countries such as Austria (AT) and the Czech Republic (CZ). Mapping fire ignition probabilities across countries can be a useful tool for fire risk mitigation. This study was conducted to: (i) evaluate the contribution of the variables obtained from open-source datasets (i.e., MODIS, OpenStreetMap, and WorldClim) for modeling fire ignition probability at the country level; and (ii) investigate how well the Random Forest (RF) method performs from one country to another. The importance of the predictors was evaluated using the Gini impurity method, and RF was evaluated using the ROC-AUC and confusion matrix. The most important variables were the topographic wetness index in the AT model and slope in the CZ model. The AUC values in the validation sets were 0.848 (AT model) and 0.717 (CZ model). When the respective models were applied to the entire dataset, they achieved 82.5% (AT model) and 66.4% (CZ model) accuracy. Cross-comparison revealed that the CZ model may be successfully applied to the AT dataset (AUC = 0.808, Acc = 82.5%), while the AT model showed poor explanatory power when applied to the CZ dataset (AUC = 0.582, Acc = 13.6%). Our study provides insights into the effect of the accuracy and completeness of open-source data on the reliability of national-level forest fire probability assessment.
Keywords: machine learning; MODIS; OpenStreetMap; random forest; forest fire occurrence mapping; WorldClim (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:6:p:5269-:d:1098934
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