Akademik Veri Yönetim Sistemi
JOURNAL OF SUSTAINABLE FORESTRY, 2026 (SCI-Expanded, Scopus)
Forest fires pose significant threats to ecosystems, human settlements, and biodiversity. Therefore, a thorough understanding of fire dynamics is essential for developing effective management strategies. Existing studies primarily focus on risk mapping, susceptibility assessment, and fire behavior prediction, often overlooking the complex causal interdependencies involved in fire dynamics. Hence, this study proposes a fuzzy cognitive map (FCM) framework to analyze the factors influencing the spread and growth of forest fires. The FCM approach is selected for its ability to model complex causal relationships, integrate expert knowledge, and handle the uncertainty and vagueness that traditional deterministic models often fail to capture. Within the model, five main factors are defined: "meteorological conditions," "topographic conditions," "vegetation and fuel characteristics," "deficiencies in forest management and planning," and "intervention capacity and indirect human impacts." Each main factor is further divided into various subfactors. The model input data are obtained through consultations with experts. The FCM approach is used to analyze the causal relationships among these factors and determine their relative importance. According to the modeling results, the three most influential factors are "lack of fire corridors and barriers," "fuel density and litter layer accumulation," and "incorrect intervention strategies and coordination issues." Additionally, a sensitivity analysis is performed by comparing results from the sigmoid function with those from the hyperbolic tangent function. The value of this study lies in presenting a structured, expert-based FCM framework that clarifies how the key factors influencing forest fire spread and growth interact with one another. The findings of this study provide valuable insights for policymakers, forest administrators, and emergency response teams to develop effective prevention and mitigation measures.