Aerial Forest Fire Detection and Monitoring Using a Small UAV
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
 J. R. Martinez-de Dios, B. C. Arrue, A. Ollero, L. Merino, and F. Gómez-Rodríguez, “Computer vision techniques for forest fire perception,” Image Vis. Comput., vol. 26, no. 4, pp. 550–562, 2008.
 M. A. Akhloufi, N. A. Castro, A. Couturier, M. A. Akhloufi, N. A. Castro, and A. Couturier, “UAVs for wildland fires,” in Autonomous Systems: Sensors, Vehicles, Security, and the Internet of Everything, 2018, vol. 10643, no. May, pp. 1–14.
 C. Yuan, Z. Liu, and Y. Zhang, “Fire Detection Using Infrared Images for UAV-based Forest Fire Surveillance,” in 2017 International Conference on Unmanned Aircraft Systems, ICUAS 2017, 2017, pp. 567–572.
 L. Zhang, B. Wang, W. Peng, C. Li, Z. Lu, and Y. Guo, “Forest fire detection solution based on UAV aerial data,” Int. J. Smart Home, vol. 9, no. 8, pp. 239–250, 2015.
 B. R. Christensen, “Use of UAV or remotely piloted aircraft and forward-looking infrared in forest, rural and wildland fire management: evaluation using simple economic analysis,” New Zeal. J. For. Sci., vol. 45, no. 1, 2015.
 C. Yuan, Y. Zhang, and Z. Liu, “A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques,” Can. J. For. Res., vol. 45, no. 7, pp. 783–792, 2015.
 P. Chamoso, A. González-Briones, F. De La Prieta, and J. M. Corchado, “Computer vision system for fire detection and report using UAVs,” in Robust Solutions for Fire Fighting (RSFF’18), 2018, vol. 2146, pp. 40–49.
 S. Ma, Y. Zhang, J. Xin, Y. Yi, D. Liu, and H. Liu, “An Early Forest Fire Detection Method Based on Unmanned Aerial Vehicle Vision,” in Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018, 2018, pp. 6344–6349.
 C. Yuan, Z. Liu, and Y. Zhang, “Learning-Based Smoke Detection for Unmanned Aerial Vehicles Applied to Forest Fire Surveillance,” J. Intell. Robot. Syst. Theory Appl., pp. 1–13, 2018.
 C. Yuan, Z. Liu, and Y. Zhang, “Aerial Images-Based Forest Fire Detection for Firefighting Using Optical Remote Sensing Techniques and Unmanned Aerial Vehicles,” J. Intell. Robot. Syst. Theory Appl., vol. 88, no. 2–4, pp. 635–654, 2017.
 C. Yuan, Z. Liu, and Y. Zhang, “Vision-based forest fire detection in aerial images for firefighting using UAVs,” 2016 Int. Conf. Unmanned Aircr. Syst. ICUAS 2016, pp. 1200– 1205, 2016.
 C. E. Premal and S. S. Vinsley, “Image Processing Based Forest Fire Detection,” Int. J. Emerg. Technol. Adv. Eng., vol. 2, no. 2, pp. 87–95, 2014.
 H. Cruz, M. Eckert, J. Meneses, and J. F. Martínez, “Efficient forest fire detection index for application in Unmanned Aerial Systems (UASs),” Sensors, vol. 16, no. 6, 2016.
 G. F. M. Center(GFMC), “Firebird 2001 Fire Fighting Management Support System,” 2001.
 J. R. M. de Dios, L. Merino, F. Caballero, and A. Ollero, “Automatic forest-fire measuring using ground stations and unmanned aerial systems,” Sensors, vol. 11, no. 6, pp. 6328–6353, 2011.
 E. Pastor, C. Barrado, P. Royo, E. Santamaria, J. Lopez, and E. Salami, “Architecture for a helicopter- based unmanned aerial systems wildfire surveillance system,” Geocarto Int., vol. 26, no. 2, pp. 113–131, 2011.
 K. Alexis, G. Nikolakopoulos, A. Tzes, and L. Dritsas, “Coordination of Helicopter UAVs for Aerial Forest- Fire Surveillance,” Appl. Intell. Control to Eng. Syst., pp. 169–193, 2009.
 W. Krüll, R. Tobera, I. Willms, H. Essen, and N. Von Wahl, “Early forest fire detection and verification using optical smoke, gas and microwave sensors,” Procedia Eng., vol. 45, pp. 584–594, 2012.
 L. Merino, F. Caballero, J. R. Martínez-de Dios, J. Ferruz, and A. Ollero, “A cooperative perception system for multiple UAVs: Application to automatic detection of forest fires,” J. F. Robot., vol. 23, no. 3–4, pp. 165–184, 2006.
 D. W. Casbeer, D. B. Kingston, R. W. Beard, and T. W. Mc lain, “Cooperative forest fire surveillance using a team of small unmanned air vehicles,” Int. J. Syst. Sci., vol. 37, no. 6, pp. 351–360, 2006.
 H. X. Pham, H. M. La, D. Feil-Seifer, and M. Deans, “A distributed control framework for a team of unmanned aerial vehicles for dynamic wildfire tracking,” in IEEE International Conference on Intelligent Robots and Systems, 2017, pp. 6648–6653.
 A. Ford and A. Roberts, “Colour Space Conversions,” 1998.
 P. Gunjal, B. Gunjal, H. Shinde, S. Vanam, and S. Aher, “Moving Object Tracking Using Kalman Filter,” in International Conference On Advances in Communication and Computing Technology (ICACCT), 2018, pp. 544–547.
 G. Cai, B. Chen, and T. Lee, “Coordinate Systems and Transformations,” in Unmanned Rotorcraft Systems, London: Springer, 2011, pp. 23–34.
 Mathworks, “Fundamental Coordinate System Concepts.”
 H. Vermeille, “An analytical method to transform geocentric into geodetic coordinates,” J. Geod., vol. 85, pp. 105–117, 2011.
 DJI, “DJI-NAZA-M V2.” .