A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques
Top Cited Papers
- 1 July 2015
- journal article
- review article
- Published by Canadian Science Publishing in Canadian Journal of Forest Research
- Vol. 45 (7), 783-792
- https://doi.org/10.1139/cjfr-2014-0347
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.Keywords
This publication has 91 references indexed in Scilit:
- Multisensor Network System for Wildfire Detection Using Infrared Image ProcessingThe Scientific World Journal, 2013
- Automatic Forest-Fire Measuring Using Ground Stations and Unmanned Aerial SystemsSensors, 2011
- Video Fire Smoke Detection Using Motion and Color FeaturesFire Technology, 2009
- A fast accumulative motion orientation model based on integral image for video smoke detectionPattern Recognition Letters, 2008
- Computer vision techniques for forest fire perceptionImage and Vision Computing, 2008
- Fire detection using statistical color model in video sequencesJournal of Visual Communication and Image Representation, 2007
- Unmanned aerial vehicles as tools for forest-fire fightingForest Ecology and Management, 2006
- Design of a dedicated parallel processor for the prediction of forest fire spreading using cellular automata and genetic algorithmsEngineering Applications of Artificial Intelligence, 2004
- Flame recognition in videoPattern Recognition Letters, 2002
- Techniques for reducing false alarms in infrared forest-fire automatic detection systemsControl Engineering Practice, 1999