Natural Hazards

, Volume 35, Issue 3, pp 361–376 | Cite as

Active Fire Detection for Fire Emergency Management: Potential and Limitations for the Operational Use of Remote Sensing

  • Jesus San-Miguel-AyanzEmail author
  • Nicolas Ravail


The use of the mid-infrared and thermal bands of sensors on board airborne platforms and satellites permits the detection of active fires on the Earth’s surface. This application has been available to the fire-fighting community for many years. However, limitations in the fire detection capabilities of the sensors and/or the lack of adequate re-visit frequency have prevented the use of these systems for operational forest fire-fighting. In addition to mobile systems, remote sensors positioned on fixed fire-watch towers have also been used for active fire detection. These instruments are often positioned in strategic look-out places to provide continuous monitoring of the surrounding areas. They locate fires through the detection of either hot spots (areas of increased temperature in comparison to the background) or smoke plumes produced by the fires. This article evaluates the use of existing remote sensing systems for active fire detection, with emphasis on the applicability of these systems for fire emergency management and fire-fighting. Long-range remote sensing devices on board satellites are considered, airborne systems are assessed, and short-range fire detection instruments on fixed ground platforms are reviewed. A short introduction to forthcoming satellite systems, which will be based on the combined use of several small satellites, is presented. The advantages and drawbacks of the different systems are evaluated from a fire management perspective.


active fire early fire detection remote sensing satellite systems infrared spectrum 


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  1. Arino, O., Melinotte, J.M. 1995Fire Index Atlas, Earth ObserQuart.501116Google Scholar
  2. Arino, O., Melinotte J.M., Calabresi, G.: 1993, Fire, cloud, land, water: The ‘Ionia’AVHRR CD-Browser of ESRIN. EOQ 41, ESA, EST EC, Noordwijk, July 1993.Google Scholar
  3. Arrue, B.C., Ollero, A., Martinez-deDios J., R. 2000An intelligent system for false alarm reduction in infrared detection of forest firesIEEE Intell. Syst.156473CrossRefGoogle Scholar
  4. Boles, S.H., Verbyla, D.L. 1999Effect of scan angle on AVHRR fire detection accuracy in interior AlaskaInt. J. Remote Sens.2034373443CrossRefGoogle Scholar
  5. Brieb, K., Barwald, W., Gerlich, T., Jahn, H., Lura, F., Studemund, H. 2000The DLR small satellite mission BIRDActa Astronaut.46111120CrossRefGoogle Scholar
  6. Brieb, K., Jahn, H., Ginati, A., Sommer, K. 1996A small satellite solution for the fire detection and monitoring from spaceActa Astronaut.39447457CrossRefGoogle Scholar
  7. Cahoon, D.R., Stocks, B.J., Alexander, M.E., Baum, B.A., Goldammer, J.G. 2000Wildland fire detection from space: Theory and applicationInnes, L.J.Beniston, M.Verstraete, M.M. eds. Biomass Burning and its Inter-Relationships with the Climate System.Kluwer Academic PublishersThe NetherlandsGoogle Scholar
  8. Chuvieco, E., Martin, P. 1994A simple method for fire growth mapping using AVHRR channel 3 dataInt. J. Remote Sens.1531413146Google Scholar
  9. De Vries J.S., Kemp R.A.W., (1994). Results with a Multi-sprectral autonomous wildfire detection system. Proceedings of the 2nd International Conference on Forest Fire Research. Vol II. CP.27, pp. 779–791.Google Scholar
  10. Dwyer, E., Pinnock, S., Gregoire, J.-M., Pereira, J.M. 2000Global and temporal distribution of vegetation fire as determined from satellite imageryInt. J. Remote Sens.2112891302CrossRefGoogle Scholar
  11. Elvidge, C.D., Hobson, V.R., Baugh, K.E., Dietz, J.B., Shimabujuro, Y.E., Krug, T., Novo, E.M., L., M., Echevarria, F.R. 2001DMSP-OLS estimation of tropical forest area impated by surface fires in Roraima, Brazil: 1995 versus 1998Int. J. Remote Sens.2226612673CrossRefGoogle Scholar
  12. ESA, 2000, REMSAT, Space Agency, ESA-ESRIN, Via Galileo s/n, Frascati, Italy.Google Scholar
  13. European Commission: 1996, Forest Fires in Southern Europe, Office for Official Publications of the European Communities, L-2985, Luxemburg.Google Scholar
  14. Flasse, S.P., Ceccato, P. 1996A contextual algorithm for AVHRR fire detectionInt. J. Remote Sens.17419424Google Scholar
  15. Giglio, L, Kendall, J.D., Justice, C.O. 1999Evaluation of global fire detection algorithms using simulated AVHRR infrared dataInt. J. Remote Sens.2019471985CrossRefGoogle Scholar
  16. Gómez-Rodríguez, F., Pascual-Peña, S., Arrue B.C., Ollero, A.: 2002, Smoke Detection Using Image Processing. IV International Congress on Forest Fire Research - IV ICFFR 2002 & Wildland Fire Safety. ISBN: 90-77017-72-0.Google Scholar
  17. INSA.: 2000, FUEGO Instrument Design, Prototype, Construction and Validation, FUEGO 2 Final Report, INSA publications, Madrid, Spain.Google Scholar
  18. Justice, C.O., Giglio, L., Korontzi, S., Owens, J., Morissette, J.T., Roy, D., Descloitres, J., Alleaume, S., Petitcolin, F., Kaufman, Y. 2002The MODIS fire productsRemote Sens. Environ.83244262CrossRefGoogle Scholar
  19. Kaiser, T. and Kempka, T.: 2001, Is microwave radiation useful for fire detection?, In: Beall, K., Grosshandler, W., Luck, H. (eds.), Proceedings of the International Conference on Automatic Fire Detection, held in Maryland on March 25–28.Google Scholar
  20. Kaufman, Y.J., Tucker, C.J., Fung, I. 1990Remote sensing of biomass burning in the tropicsJ. Geophys. Res.9599279939Google Scholar
  21. Kaufman, Y.J., Justice, C.O., Flynn, L.P., Kendall, J.D., Prins, E.M., Giglio, L., Ward, D.E., Menzel, W.P., Setzer, A.W. 1998Potential globe fire monitoring from EOS-MODISJ.Geophys.Res.1033221532238CrossRefGoogle Scholar
  22. Kelha, V., Rauste, T., Hame, T., Septon, T., Buongiorno, A., Frauenberger, O., Soini, K., Venäläinen, A., San Miguel-Ayanz, J., Vainio, T.: 2001, Promotion of space tecnologies for supporting the management of natural disasters: Earth observation technologies for decision support ‘Fire Risk Management in Finland, Final report to the European Space Agency, VTT Automation, Espoo, Finland.Google Scholar
  23. Kennedy, P.J., Belward, A.S., Gregoire, J.M. 1994An improved approach to fire monitoring in West Africa using AVHRR dataInt. J. Remote Sens.1522352255Google Scholar
  24. Langaas, S. 1993A parametrised bispectral model for savanna fire detection using AVHRR night imagesInt. J. Remote Sens.1422452262Google Scholar
  25. Li, Z., Nadon, S., Cihlar, J. 2000Satellite-based detection of Canadian boreal forest fire: Development and application of the algorithmInt. J. Remote Sens.2130573069CrossRefGoogle Scholar
  26. Li, Z., Khananian, A., Fraser, R., Cihlar, J. 2001Automatic Detection of Fire Smoke Using Artificial Neural Networks and Threshold Approaches Applied to AVHRR ImageryIEEE T. Geosci. Remote Sens.3918591870CrossRefGoogle Scholar
  27. Ollero, B.C., Arrue, A., Martinez, J.R., . Murillo, J.J. 1999Techniques for reducing false alarms in infrared forest-fire automatic detection systemsControl Eng. Pract.7123131CrossRefGoogle Scholar
  28. Prins, E.M., Menzel, W.P. 1992Geostationary Satellite detection of biomass Burning in South AmericaInt. J. Remote Sens.1327832799Google Scholar
  29. Prins, E.M., Menzel, W.P. 1994Trends in South American biomass burning detected with the GOES visible infrared spin scan radiometer atmospheric sounder from 1983 to 1991J.Geophys.Res.9971916735CrossRefGoogle Scholar
  30. Prins, E.M., Menzel, W.P. 1996Investigation of biomass burning and aerosol loading and transport utilizing geostationary satellite dataLevine, J.S. eds. Biomass Burning and Global Change.The MIT PressCambridge MA6572Google Scholar
  31. Ravail, N. and San-Miguel-Ayanz: 2002, Evaluation of the performance of the world fire web contextual fire detection algorithm over Spain for the years 1997–98, EUR Report, Office for Official Publications of the European Communities, L-2985, Luxemburg.Google Scholar
  32. Robinson, J.M. 1991Fire from space: Global evaluation using infrared remote sensingInt. J. Remote Sens.12324Google Scholar
  33. Sadovnik L.S., Manasson V.A., Mino, M., Kiseliov, V.: 1999, Remote fire detection using MMW radiometric sensor, In: M. N. Armenise, P.A. Pecorella, L. S. Sadovnik, (eds.), Optical Devices & Methods for Microwave/Millimeter-wave & Frontier Applications, SPIE Society of Photo-Optical Instrumentation Engineering, May, 1999, pp. 73–80.Google Scholar
  34. Stroppiana, D., Pinnock, S., Gregoire, J.-M. 2000The global fire product: Daily fire occurrence from April 1992 to December 1993 derived from NOAA AVHRR dataInt. J. Remote Sens.2112791288Google Scholar
  35. Utkin A.B., Fernandes, A., Simoes, F., Vilar, R., Lavrov, A.: 2002, Forest-fire Detection by Means of Lidar. Forest Fire Research & Wildland Fire Safety.Google Scholar
  36. Wybo J.L., Eftichidis, G., Koutsouris, D., Manganas, T., Viegas D.X., Apostolopoulos, T., Pelosio, E., Bovio, G., Ollero, A. Schmidt, D., Criado, A.: 1998, DEDICS: A general supporting management of forest Fire Proceedings of the 3rd International Conference on Forest Fire Research. Luso, Portugal, November 1998. pp. 2003–2012.Google Scholar

Copyright information

© Springer 2005

Authors and Affiliations

  1. 1.Institute for Environment and SustainabilityEuropean Commission DG Joint Research CentreIspra

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