KnE Engineering
ISSN: 2518-6841
The latest conference proceedings on all fields of engineering.
Aerial Forest Fire Detection and Monitoring Using a Small UAV
Published date: Jun 02 2020
Journal Title: KnE Engineering
Issue title: International Congress on Engineering — Engineering for Evolution
Pages: 242–256
Authors:
Abstract:
In recent years, large patches of forest have been destroyed by fires, bringing tragic consequences for the environment and small settlements established around these regions. In this context, it is essential that fire fighting teams possess an increased situational awareness about the fire propagation, in order to promptly act in the extinguishing process. Recent advances in UAV technology allied with remote sensing and computer vision techniques show very promising UAVs applicability in forest fires detection and monitoring. Besides presenting lower operational costs, these vehicles are able to reach regions that are inaccessible or considered too dangerous for fire fighting crews operations. This paper describes the application of a real-time forest fire detection algorithm using aerial images captured by a video camera onboard an Unmanned Aerial Vehicle (UAV). The forest fire detection algorithm consists of a rule-based colour model that uses both RGB and YCbCr colour spaces to identify fire pixels. An intuitive targeting system was also developed, allowing the detection of multiple fires at the same time. Additionally, a fire geolocation algorithm was developed in order to estimate the fire location in terms of latitude (φ), longitude (λ) and altitude (h). The geolocation algorithm consists of applying two coordinates systems transformations between the body-fixed frame, North-East-Down frame (NED) and Earth-Centered, Earth Fixed (ECEF) frame. Flight tests were performed during a controlled burn in order to assess the fire detection algorithm performance. The algorithm was able to detect the fire with few false positive detections.
Keywords: Aerial fire detection algorithm, Aerial fire monitoring, Forest fire, UAV, Remote sensing
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