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Country-Level Modeling of Forest Fires in Austria and the Czech Republic: Insights from Open-Source Data

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43410%2F23%3A43923417" target="_blank" >RIV/62156489:43410/23:43923417 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://doi.org/10.3390/su15065269" target="_blank" >https://doi.org/10.3390/su15065269</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3390/su15065269" target="_blank" >10.3390/su15065269</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Country-Level Modeling of Forest Fires in Austria and the Czech Republic: Insights from Open-Source Data

  • Popis výsledku v původním jazyce

    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.

  • Název v anglickém jazyce

    Country-Level Modeling of Forest Fires in Austria and the Czech Republic: Insights from Open-Source Data

  • Popis výsledku anglicky

    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.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    40102 - Forestry

Návaznosti výsledku

  • Projekt

  • Návaznosti

    O - Projekt operacniho programu

Ostatní

  • Rok uplatnění

    2023

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Sustainability

  • ISSN

    2071-1050

  • e-ISSN

    2071-1050

  • Svazek periodika

    15

  • Číslo periodika v rámci svazku

    6

  • Stát vydavatele periodika

    CH - Švýcarská konfederace

  • Počet stran výsledku

    20

  • Strana od-do

    5269

  • Kód UT WoS článku

    000958145700001

  • EID výsledku v databázi Scopus