Canadian Journal of Forest Research· 2015Q1· Review
A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques
- 625citations
- Q1SCImago
- 2015year
Short summary
This paper surveys current progress in using unmanned aerial vehicles (UAVs) equipped with vision-based systems for forest fire monitoring, detection, and fighting, highlighting their potential due to maneuverability, range, and safety.
AI-generated from the title and abstract; the full text is not read.
Key points
- UAVs offer advantages in maneuverability, operational range, and personnel safety for forest fire management.
- Key technologies reviewed include fire detection, diagnosis, prognosis, image vibration elimination, and cooperative UAV control.
- The survey outlines existing challenges and potential solutions for applying UAVs in firefighting.
- The paper provides a systematic overview of progress in this rapidly developing field.
AI-generated from the title and abstract; the full text is not read.
Abstract
Because of their rapid maneuverability, extended operational range, and improved personnel safety, unmanned aerial vehicles (UAVs) with vision-based systems have great potential for monitoring, detecting, and fighting forest fires. Over the last decade, UAV-based forest fire fighting technology has shown increasing promise. This paper presents a systematic overview of current progress in this field. First, a brief review of the development and system architecture of UAV systems for forest fire monitoring, detection, and fighting is provided. Next, technologies related to UAV forest fire monitoring, detection, and fighting are briefly reviewed, including those associated with fire detection, diagnosis, and prognosis, image vibration elimination, and cooperative control of UAVs. The final section outlines existing challenges and potential solutions in the application of UAVs to forest firefighting.
The authors' abstract, as published at the source. Canadian Journal of Forest Research, 2015 · DOI ↗
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