TY  - JOUR
AU  - Milanović, Slobodan
AU  - Trailović, Zoran
AU  - Milanović, Slađan
AU  - Hochbichler, Eduard
AU  - Kirisits, Thomas
AU  - Immitzer, Markus
AU  - Čermák, Petr
AU  - Pokorný, Radek
AU  - Jankovský, Libor
AU  - Jaafari, Abolfazl
PY  - 2023
UR  - http://rimi.imi.bg.ac.rs/handle/123456789/1315
AB  - 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.
PB  - Multidisciplinary Digital Publishing Institute (MDPI)
T2  - Sustainability
T2  - Sustainability
T1  - Country-Level Modeling of Forest Fires in Austria and the Czech Republic: Insights from Open-Source Data
IS  - 6
SP  - 5269
VL  - 15
DO  - 10.3390/su15065269
ER  - 

@article{
author = "Milanović, Slobodan and Trailović, Zoran and Milanović, Slađan and Hochbichler, Eduard and Kirisits, Thomas and Immitzer, Markus and Čermák, Petr and Pokorný, Radek and Jankovský, Libor and Jaafari, Abolfazl",
year = "2023",
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.",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
journal = "Sustainability, Sustainability",
title = "Country-Level Modeling of Forest Fires in Austria and the Czech Republic: Insights from Open-Source Data",
number = "6",
pages = "5269",
volume = "15",
doi = "10.3390/su15065269"
}

Milanović, S., Trailović, Z., Milanović, S., Hochbichler, E., Kirisits, T., Immitzer, M., Čermák, P., Pokorný, R., Jankovský, L.,& Jaafari, A.. (2023). Country-Level Modeling of Forest Fires in Austria and the Czech Republic: Insights from Open-Source Data. in Sustainability
Multidisciplinary Digital Publishing Institute (MDPI)., 15(6), 5269.
https://doi.org/10.3390/su15065269

Milanović S, Trailović Z, Milanović S, Hochbichler E, Kirisits T, Immitzer M, Čermák P, Pokorný R, Jankovský L, Jaafari A. Country-Level Modeling of Forest Fires in Austria and the Czech Republic: Insights from Open-Source Data. in Sustainability. 2023;15(6):5269.
doi:10.3390/su15065269 .

Milanović, Slobodan, Trailović, Zoran, Milanović, Slađan, Hochbichler, Eduard, Kirisits, Thomas, Immitzer, Markus, Čermák, Petr, Pokorný, Radek, Jankovský, Libor, Jaafari, Abolfazl, "Country-Level Modeling of Forest Fires in Austria and the Czech Republic: Insights from Open-Source Data" in Sustainability, 15, no. 6 (2023):5269,
https://doi.org/10.3390/su15065269 . .