FOREST FIRE SUSCEPTIBILITY ASSESSMENT WITH MACHINE LEARNING METHODS IN NORTH-EAST TURKIYE

12 citations as recorded by crossref.

1. Mapping climate change induced forest fire susceptibility using tree-based machine learning algorithms in Bangladesh M. Haydar et al. https://doi.org/10.1016/j.ecolind.2025.113657
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5. Analysis of Stand Parameters in Burned and Unburned Areas Within Wildfire Boundaries Using Grey Wolf Optimization: A Case Study of the 2025 Türkiye T. Çınar https://doi.org/10.58816/duzceod.1904445
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7. Integrating geospatial, remote sensing, and machine learning for climate-induced forest fire susceptibility mapping in Similipal Tiger Reserve, India C. Singha et al. https://doi.org/10.1016/j.foreco.2024.121729
8. Temporal–Spatial Characteristics and Influencing Factors of Forest Fires in the Tropic of Cancer (Yunnan Section) H. Xu et al. https://doi.org/10.3390/f15040661
9. Modeling of Forest Fire Risk Areas of Amazonas Department, Peru: Comparative Evaluation of Three Machine Learning Methods A. Vergara et al. https://doi.org/10.3390/f16020273
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