Clustered-map probabilistic cellular automata for fire propagation in the Brazilian Cerrado with heterogeneous vegetation and wind interference

Author:

Brasiel Heitor Castro,Lima Danielli Araújo

Abstract

<abstract><p>Wildfires pose a significant threat to both biodiversity and human communities, and understanding their behavior and the rate at which they burn through different vegetation types is crucial for effective management and conservation. In this research, we present a comprehensive analysis of wildfire behavior and vegetation burning rates in the unique ecosystem of Sete Cidades National Park. To achieve this, we adopt a qualiquantitative approach that combines both qualitative and quantitative methodologies, considering the multifaceted variables at play, including wind conditions, various vegetation types, and the dynamics of fire progression. We conducted an extensive dataset comprising $ 100 $ simulations for each of three distinct scenarios, ensuring robustness in our data for statistical analysis. By incorporating qualitative data obtained through field observations and expert opinions, we gain a deeper understanding of the contextual nuances specific to Sete Cidades National Park. This approach enriches the interpretation of our quantitative results, providing valuable context and real-world relevance. Our materials include a cellular automaton lattice with $ 200 \times 200 $ cells, representing the diverse landscape of the study area. We used MATLAB to visualize this landscape, generating distinct representations of the scenarios. Our findings reveal the distribution of different vegetation types across these scenarios, emphasizing the resilience of Rupestrian Cerrado, the diversity of Typical Cerrado, and the importance of Riparian Forest in preserving aquatic ecosystems. This research contributes to the broader understanding of wildfire management, considering the interdisciplinary aspects of environmental science, forestry, and meteorology. By integrating knowledge from diverse fields, we provide a holistic analysis that can inform effective conservation strategies and wildfire management practices.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Reference45 articles.

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