Articles | Volume 10, issue 6
https://doi.org/10.5194/amt-10-2299-2017
https://doi.org/10.5194/amt-10-2299-2017
Research article
 | 
22 Jun 2017
Research article |  | 22 Jun 2017

Forest Fire Finder – DOAS application to long-range forest fire detection

Rui Valente de Almeida and Pedro Vieira

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Revised manuscript not accepted
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Cited articles

Alkhatib, A. A. A.: A review on forest fire detection techniques, International Journal of Distributed Sensor Networks, 2014, 597368, https://doi.org/10.1155/2014/597368, 2014.
Bevington, P. R. and Robinson, D. K.: Data Reduction and Error Analysis for the Physical Sciences, 2003.
BNHCRC: Bushfire & Natural Hazards CRC, available at: http://www.bnhcrc.com.au/home, last access: 10 May 2016.
Bogumil, K., Orphal, J., Homann, T., Voigt, S., Spietz, P., Fleischmann, O., Vogel, A., Hartmann, M., Kromminga, H., Bovensmann, H., Frerick, J., and Burrows, J.: Measurements of molecular absorption spectra with the SCIAMACHY pre-flight model: instrument characterization and reference data for atmospheric remote-sensing in the 230–2380 nm region, J. Photoch. Photobio. A, 157, 167–184, https://doi.org/10.1016/S1010-6030(03)00062-5, 2003.
Boser, B. E., Guyon, I. M., and Vapnik, V. N.: A training algorithm for optimal margin classifiers, in: Proceedings of the fifth annual workshop on Computational learning theory – COLT '92, ACM Press, New York, New York, USA, 144–152, https://doi.org/10.1145/130385.130401, 1992.
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This paper presents the Forest Fire Finder (FFF) System, a long range forest fire detection system. It works by detecting a smoke column above the horizon, by analysing the light that goes through it. In the article, you will find a technical description and an analysis of the behaviour of 13 of these devices, which were installed in a Portuguese national park. We conclude that the deployed FFF network managed to detect more that 200 fires, proving the system to be effective in fire detection.