Proof of Concept: Multi-Target Wildfire Risk Prediction and Large Language Model Synthesis

• URL: http://arxiv.org/abs/2601.11686v1
• Date: Fri, 16 Jan 2026 10:47:13 GMT
• Title: Proof of Concept: Multi-Target Wildfire Risk Prediction and Large Language Model Synthesis
• Authors: Nicolas Caron, Christophe Guyeux, Hassan Noura, Benjamin Aynes,
• Abstract summary: Current state-of-the-art approaches to wildfire risk assessment often overlook operational needs, limiting their practical value for first responders and firefighting services.<n>We propose the development of a hybrid framework that combines predictive models for each risk dimension with large language models (LLMs) to synthesize heterogeneous outputs into structured, actionable reports.
• Score: 2.2049183478692593
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Current state-of-the-art approaches to wildfire risk assessment often overlook operational needs, limiting their practical value for first responders and firefighting services. Effective wildfire management requires a multi-target analysis that captures the diverse dimensions of wildfire risk, including meteorological danger, ignition activity, intervention complexity, and resource mobilization, rather than relying on a single predictive indicator. In this proof of concept, we propose the development of a hybrid framework that combines predictive models for each risk dimension with large language models (LLMs) to synthesize heterogeneous outputs into structured, actionable reports.

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