T. Remmel

Integrating Explainable Machine Learning and Classification methods for Wildland Fire Danger Mapping

Abstract. In the context of contemporary wildland fire management, accurately understanding and predicting fire danger is fundamental to ensuring public safety and optimizing the allocation of suppression resources. Geospatial data combined with machine learning provides an effective framework for analyzing the complex...