Advancing Early Wildfire Detection: Integration of Vision Language Models with Unmanned Aerial Vehicle Remote Sensing for Enhanced Situational Awareness

Seidel L, Gehringer S, Raczok T, Ivens SN, Eckardt B, März M (2025)

Publication Type: Journal article

Publication year: 2025

Book Volume: 9

Article Number: 347

Journal Issue: 5

DOI: 10.3390/drones9050347

Abstract

Early wildfire detection is critical for effective suppression efforts, necessitating rapid alerts and precise localization. While computer vision techniques offer reliable fire detection, they often lack contextual understanding. This paper addresses this limitation by utilizing Vision Language Models (VLMs) to generate structured scene descriptions from Unmanned Aerial Vehicle (UAV) imagery. UAV-based remote sensing provides diverse perspectives for potential wildfires, and state-of-the-art VLMs enable rapid and detailed scene characterization. We evaluated both cloud-based (OpenAI, Google DeepMind) and open-weight, locally deployed VLMs on a novel evaluation dataset specifically curated for understanding forest fire scenes. Our results demonstrate that relatively compact, fine-tuned VLMs can provide rich contextual information, including forest type, fire state, and fire type. Specifically, our best-performing model, ForestFireVLM-7B (fine-tuned from Qwen2-5-VL-7B), achieved a 76.6% average accuracy across all categories, surpassing the strongest closed-weight baseline (Gemini 2.0 Pro at 65.5%). Furthermore, zero-shot evaluation on the publicly available FIgLib dataset demonstrated state-of-the-art smoke detection accuracy using VLMs. Our findings highlight the potential of fine-tuned, open-weight VLMs for enhanced wildfire situational awareness via detailed scene interpretation.

Authors with CRIS profile

Martin März Lehrstuhl für Leistungselektronik (LEE)

Involved external institutions

Fraunhofer-Institut für Integrierte Systeme und Bauelementetechnologie (IISB) DE Germany (DE) Fraunhofer-Institut für Integrierte Schaltungen (IIS) DE Germany (DE)

How to cite

APA:

Seidel, L., Gehringer, S., Raczok, T., Ivens, S.N., Eckardt, B., & März, M. (2025). Advancing Early Wildfire Detection: Integration of Vision Language Models with Unmanned Aerial Vehicle Remote Sensing for Enhanced Situational Awareness. , 9(5). https://doi.org/10.3390/drones9050347

MLA:

Seidel, Leon, et al. "Advancing Early Wildfire Detection: Integration of Vision Language Models with Unmanned Aerial Vehicle Remote Sensing for Enhanced Situational Awareness." 9.5 (2025).

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