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

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

40102 - Forestry

Project

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Continuities

O - Projekt operacniho programu

Publication year

2023

Confidentiality

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

Name of the periodical

Sustainability

ISSN

2071-1050

e-ISSN

2071-1050

Volume of the periodical

15

Issue of the periodical within the volume

6

Country of publishing house

CH - SWITZERLAND

Number of pages

20

Pages from-to

5269

UT code for WoS article

000958145700001

EID of the result in the Scopus database

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