Determining Forest Fire Position from UAV Photogrammetry using Color Filtration Algorithm

Abdul Muid - Universitas Tanjungpura, Jl. Prof. Dr. Hadari Nawawi, Pontianak 78124, Indonesia
Maria Evita - Institut Teknologi Bandung, Jl. Ganesha 10 Bandung 40132, Indonesia
Nina Aminah - Institut Teknologi Bandung, Jl. Ganesha 10 Bandung 40132, Indonesia
Maman Budiman - Institut Teknologi Bandung, Jl. Ganesha 10 Bandung 40132, Indonesia
Mitra Djamal - Institut Teknologi Bandung, Jl. Ganesha 10 Bandung 40132, Indonesia

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Forest fires frequently happen worldwide, especially in the dry season. A forest fire early warning system (EWS) is needed to prevent this disaster. The main part of EWS is the hotspot detection system. On the other side, Unmanned Aerial Vehicle (UAV) technology offers an alternative solution to detect the hotspot for poor satellite image processing accuracy. Remote sensing techniques with UAV working drones are progressively challenging. Drones can provide results in 2D and 3D images with high resolution and real-time. Therefore, in this research, we have used a photogrammetry application from the number of images collected by a UAV with an optimum flight plan for the mission to determine the location of the forest fire. This paper describes remote sensing experiments using drones to detect land fires. The experiment was carried out using a quadcopter drone of the DJI Phantom 4 Pro. The photos are processed using Agisoft Metashape Professional image processing software and become a 2D image. These images captured a fire simulation in a known location. After a high resolution (GSD – Ground Sampling Distance – 0.87cm/px) orthophoto had been generated, a color filtration algorithm detected a hotspot to detect a fire at the exact location. The results are almost zero deviation of longitude and latitude from the real location with 1.44 m2 and 1.06 m2 fire area from 2 experiments. This algorithm program has TPR and FPR are 0,78 and 0, respectively. Further research can develop an EWS with a combination of UAV and Wireless Sensor Networks.


Unmanned Aerial Vehicle (UAV); Forest Fires Detection; Colour Filter Algorithm; High Resolution Orthophoto

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S. Darvishpoor, J. Roshanian, A. Raissi, and M. Hassanalian, "Configurations, flight mechanisms, and applications of unmanned aerial systems: A review," Progress in Aerospace Sciences, vol. 121. Elsevier Ltd, Feb. 01, 2020. doi: 10.1016/j.paerosci.2020.100694.

C. Xu, X. Liao, J. Tan, H. Ye, and H. Lu, "Recent Research Progress of Unmanned Aerial Vehicle Regulation Policies and Technologies in Urban Low Altitude," IEEE Access, vol. 8, pp. 74175–74194, 2020, doi: 10.1109/ACCESS.2020.2987622.

A. S. Saeed, A. B. Younes, C. Cai, and G. Cai, "A survey of hybrid Unmanned Aerial Vehicles," Progress in Aerospace Sciences, vol. 98. Elsevier Ltd, pp. 91–105, Apr. 01, 2018. doi: 10.1016/j.paerosci.2018.03.007.

X. Li, J. Tan, A. Liu, P. Vijayakumar, N. Kumar, and M. Alazab, "A Novel UAV-Enabled Data Collection Scheme for Intelligent Transportation System through UAV Speed Control," IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 4, pp. 2100–2110, Apr. 2021, doi: 10.1109/TITS.2020.3040557.

G. J. J. Ducard and M. Allenspach, "Review of designs and flight control techniques of hybrid and convertible VTOL UAVs," Aerospace Science and Technology, vol. 118. Elsevier Masson s.r.l., Nov. 01, 2021. doi: 10.1016/j.ast.2021.107035.

S. Das et al., "UAV-Thermal imaging and agglomerative hierarchical clustering techniques to evaluate and rank physiological performance of wheat genotypes on sodic soil," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 173, pp. 221–237, Mar. 2021, doi: 10.1016/j.isprsjprs.2021.01.014.

J. Zheng et al., "Growing status observation for oil palm trees using Unmanned Aerial Vehicle (UAV) images," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 173, pp. 95–121, Mar. 2021, doi: 10.1016/j.isprsjprs.2021.01.008.

L. Deng, Z. Mao, X. Li, Z. Hu, F. Duan, and Y. Yan, "UAV-based multispectral remote sensing for precision agriculture: A comparison between different cameras," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 146, pp. 124–136, Dec. 2018, doi: 10.1016/j.isprsjprs.2018.09.008.

"Spy in the sky," Nature, vol. 445, no. 7130, pp. 808–809, 2007, doi: 10.1038/445808a.

N. Michael et al., "Collaborative mapping of an earthquake-damaged building via ground and aerial robots," Journal of Field Robotics, vol. 29, no. 5, pp. 832–841, Sep. 2012, doi:

A. Bauranov and J. Rakas, "Designing airspace for urban air mobility: A review of concepts and approaches," Progress in Aerospace Sciences, vol. 125, p. 100726, 2021, doi:

L. G. B. Y. F. R. L. M. K. C. C. K. QUAN Quan, "Low altitude UAV traffic management:An introductory overview and proposal ," ACTA Aeronauticaet Astronautica Sinica, vol. 41, no. 1, pp. 23238–023238, 2020.

H. E. Mohamadi, N. Kara, and M. Lagha, "Heuristic-driven strategy for boosting aerial photography with multi-UAV-aided Internet-of-Things platforms," Engineering Applications of Artificial Intelligence, vol. 112, p. 104854, 2022, doi:

L. Li et al., "Ultrahigh-resolution boreal forest canopy mapping: Combining UAV imagery and photogrammetric point clouds in a deep-learning-based approach," International Journal of Applied Earth Observation and Geoinformation, vol. 107, p. 102686, 2022, doi:

J. Wang et al., "Refined micro-scale geological disaster susceptibility evaluation based on UAV tilt photography data and weighted certainty factor method in Mountainous Area," Ecotoxicology and Environmental Safety, vol. 189, p. 110005, 2020, doi:

F. de Vivo, M. Battipede, and E. Johnson, "Infra-red line camera data-driven edge detector in UAV forest fire monitoring," Aerospace Science and Technology, vol. 111, p. 106574, 2021, doi:

F. Chiabrando, F. D'Andria, G. Sammartano, and A. Spanò, "UAV photogrammetry for archaeological site survey. 3D models at the Hierapolis in Phrygia (Turkey)," Virtual Archaeology Review, vol. 9, no. 18, pp. 28–43, Jan. 2018, doi: 10.4995/var.2018.5958.

X. Li and L. Xing, "Use of Unmanned Aerial Vehicles for Livestock Monitoring based on Streaming K-Means Clustering⁎⁎This work was supported by the Australian Research Council.," IFAC-PapersOnLine, vol. 52, no. 30, pp. 324–329, 2019, doi:

T. Umar, "Applications of drones for safety inspection in the Gulf Cooperation Council construction," Engineering, Construction and Architectural Management, vol. 28, no. 9, pp. 2337–2360, Jan. 2021, doi: 10.1108/ECAM-05-2020-0369.

S. Sreenath, H. Malik, N. Husnu, and K. Kalaichelavan, "Assessment and Use of Unmanned Aerial Vehicle for Civil Structural Health Monitoring," Procedia Computer Science, vol. 170, pp. 656–663, 2020, doi:

V. A. Korolkov, K. N. Pustovalov, A. A. Tikhomirov, A. E. Telminov, and S. A. Kurakov, "Autonomous weather stations for unmanned aerial vehicles. Preliminary results of measurements of meteorological profiles," in IOP Conference Series: Earth and Environmental Science, Dec. 2018, vol. 211, no. 1. doi: 10.1088/1755-1315/211/1/012069.

W. Budiharto, E. Irwansyah, J. S. Suroso, A. Chowanda, H. Ngarianto, and A. A. S. Gunawan, "Mapping and 3D modelling using quadrotor drone and GIS software," Journal of Big Data, vol. 8, no. 1, p. 48, 2021, doi: 10.1186/s40537-021-00436-8.

V. Sherstjuk, M. Zharikova, and I. Dorovskaja, "3D Fire Front Reconstruction in UAV-Based Forest-Fire Monitoring System," in 2020 IEEE Third International Conference on Data Stream Mining & Processing (DSMP), 2020, pp. 243–248. doi: 10.1109/DSMP47368.2020.9204196.

Z. Jiao et al., "A YOLOv3-based Learning Strategy for Real-time UAV-based Forest Fire Detection," in 2020 Chinese Control And Decision Conference (CCDC), 2020, pp. 4963–4967. doi: 10.1109/CCDC49329.2020.9163816.

D. A. Umarhadi, P. Danoedoro, P. Wicaksono, P. Widayani, W. Nurbandi, and A. Juniansah, "The Comparison of Canopy Density Measurement Using UAV and Hemispherical Photography for Remote Sensing Based Mapping," in 2018 4th International Conference on Science and Technology (ICST), 2018, pp. 1–5. doi: 10.1109/ICSTC.2018.8528670.

A. Zakiyyatuddin, M. Evita, W. Srigutomo, I. Meilano, and M. Djamal, "Geospatial Survey Analysis for 3D Field and Building Mapping using DJI Drone and Intelligent Flight Battery," Journal of Physics: Conference Series, vol. 1772, no. 1, p. 012015, 2021, doi: 10.1088/1742-6596/1772/1/012015.

Z. Qiu, X. Chu, C. Calvo-Ramirez, C. Briso, and X. Yin, "Low Altitude UAV Air-to-Ground Channel Measurement and Modeling in Semiurban Environments," Wireless Communications and Mobile Computing, vol. 2017, p. 1587412, 2017, doi: 10.1155/2017/1587412.

S. Khamphilung, "Dong Ra Nang National Forest Change Detection using Multi-temporal LANDSAT 7 ETM + Imagery by Using CART Classification: Object-Oriented Approach," Current Applied Science and Technology, vol. 21, no. 2, doi: 10.14456/cast.2021.27.

M. Boon, A. Drijfhout, and S. Tesfamichael, "Comparison of a fixed-wing and Multi-rotor UAV for Environmental mapping applications: A case study," ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-2/W6, pp. 47–54, Aug. 2017, doi: 10.5194/isprs-archives-XLII-2-W6-47-2017.

T. Bonny and M. Abdelsalam, "Autonomous Navigation of UAV based on Android Smartphone," International Journal of Advanced Computer Science and Applications, Nov. 2019.

"International Handbook on Forest Fire Protection."

A. I. Filkov, T. Ngo, S. Matthews, S. Telfer, and T. D. Penman, "Impact of Australia's catastrophic 2019/20 bushfire season on communities and environment. Retrospective analysis and current trends," Journal of Safety Science and Resilience, vol. 1, no. 1, pp. 44–56, 2020, doi:

L. Kiely et al., "Assessing costs of Indonesian fires and the benefits of restoring peatland," Nature Communications, vol. 12, no. 1, p. 7044, 2021, doi: 10.1038/s41467-021-27353-x.

P. Cortez and A. Morais, "A Data Mining Approach to Predict Forest Fires using Meteorological Data," Jan. 2007.

A. A. A. Alkhatib, "A Review on Forest Fire Detection Techniques," International Journal of Distributed Sensor Networks, vol. 10, no. 3, p. 597368, Mar. 2014, doi: 10.1155/2014/597368.

A. Molina-Pico, D. Cuesta-Frau, A. Araujo, J. Alejandre, and A. Rozas, "Forest Monitoring and Wildland Early Fire Detection by a Hierarchical Wireless Sensor Network," Journal of Sensors, vol. 2016, p. 8325845, 2016, doi: 10.1155/2016/8325845.

U. Dampage, L. Bandaranayake, R. Wanasinghe, K. Kottahachchi, and B. Jayasanka, "Forest fire detection system using wireless sensor networks and machine learning," Scientific Reports, vol. 12, no. 1, p. 46, 2022, doi: 10.1038/s41598-021-03882-9.

S. Abdullah, S. Bertalan, S. Masar, A. Coskun, and I. Kale, "A wireless sensor network for early forest fire detection and monitoring as a decision factor in the context of a complex integrated emergency response system," in 2017 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS), 2017, pp. 1–5. doi: 10.1109/EESMS.2017.8052688.

A. Matese and S. di Gennaro, "Practical Applications of a Multisensor UAV Platform Based on Multispectral, Thermal and RGB High Resolution Images in Precision Viticulture," Agriculture, vol. 8, p. 116, Jul. 2018, doi: 10.3390/agriculture8070116.

M. A. Akhloufi, A. Couturier, and N. A. Castro, "Unmanned aerial vehicles for wildland fires: Sensing, perception, cooperation and assistance," Drones, vol. 5, no. 1, Mar. 2021, doi: 10.3390/drones5010015.

N. Ya'acob, M. Syamirza Mohd Najib, N. Tajudin, A. Laily Yusof, and M. Kassim, "Image Processing Based Forest Fire Detection using Infrared Camera," Journal of Physics: Conference Series, vol. 1768, no. 1, p. 012014, 2021, doi: 10.1088/1742-6596/1768/1/012014.

K. Poobalan and S. Liew, "Fire detection based on color filters and Bag-of-Features classification," in 2015 IEEE Student Conference on Research and Development (SCOReD), 2015, pp. 389–392. doi: 10.1109/SCORED.2015.7449362.

M. Jamali, N. Karimi, and S. Samavi, "Saliency Based Fire Detection Using Texture and Color Features," in 2020 28th Iranian Conference on Electrical Engineering (ICEE), 2020, pp. 1–5. doi: 10.1109/ICEE50131.2020.9260659.

M. Hasan, R. Zaman Khan, N. A. Ibraheem, M. M. Hasan, R. Z. Khan, and P. K. Mishra, "ARPN Journal of Science and Technology:: Understanding Color Models: A Review," ARPN Journal of Science and Technology, vol. 2, no. 3, 2012, [Online]. Available:

Beck K, "Colour fire hot,", Feb. 18, 2021.

Ettling B. V., "Colours of smoke and flame," Fire Arson Investig., vol. 30, 1980. , (accessed Feb. 02, 2021).

A. Hackeloeer, K. Klasing, J. M. Krisp, and L. Meng, "Georeferencing: a review of methods and applications," Ann GIS, vol. 20, no. 1, pp. 61–69, Jan. 2014, doi: 10.1080/19475683.2013.868826.


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