Natural Hazards

, Volume 35, Issue 3, pp 343–359 | Cite as

Monitoring Forest Fire Danger with Remote Sensing

  • Brigitte Leblon


Our paper presents a review of the use of remote sensing technologies for forest wildfire danger monitoring, with a particular emphasis on its applicability to fuel moisture monitoring. Remote sensing of fuel moisture was first done with NOAA-AVHRR NDVI images, but NDVI is more related to vegetation greenness rather than water stress. NOAA-AVHRR surface temperature images were also used, alone or in association with NDVI images. Both kinds of images have a limited image availability due to cloud cover. This is not the case for radar images, but their use in fuel moisture monitoring is still experimental, because of the noisy effects of several factors. Finally, the paper discusses the operational potentials and limitations of the use of each kind of satellite data for fire danger monitoring.


forest fire fire danger fuel moisture optical thermal infrared radar NOAA-AVHRR SAR ERS-1 RADARSAT-1 


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  1. Abbott, K., Leblon, B., Staples, G., Alexander, M. E., and MacLean, D.: 2002, Use of RADARSAT-1 images to map forest fuel moisture over boreal forests, In: Proc. 24th Can. Remote Sens. Symp., Toronto, June 2002, pp. 134–136.Google Scholar
  2. Aguado, I., Chuvieco, E., Salas, J. 2003Assessment of forest fire danger conditions in southern Spain from NOAA images and meteorological indicesInt. J. Remote Sens2416531668CrossRefGoogle Scholar
  3. Bastiaanssen, W. G. M., Menenti, M., Fedded, R. A., Holtslag, A. A. M. 1998A remote sensing surface energy balance algorithm for land (SEBAL) 1. FormulationJ. Hydrol.212, 213198212Google Scholar
  4. Bourgeau-Chavez, L. L., Kasischke, E. S., Rutherford, M. D. 1999Evaluation of ERS SAR data for prediction of fire danger in a boreal region, IntJ. Wildland Fire9183194Google Scholar
  5. Bourgeau-Chavez, L. L., Brunzell,S., Nolan, M., and Hyer, (ed.): 2001, Analysis of SAR data for fire danger prediction in boreal Alaska, Final Report, ASF-IARC Grant NAS-98-129, 59 p.Google Scholar
  6. Burgan, R. E., Klaver, R. W., Klaver, J. M. 1998Fuel models and fire potential from satellite and surface observations, IntJ. Wildland Fire8159170Google Scholar
  7. Camia, A., Bovio, G., Aguado, I., Stach, N. 1999Meteorological fire danger indices and remote sensingChuvieco, E. eds. Remote Sensing of Large Wildfires in the European Mediterranean BasinSpringer-VerlagBerlin3959Google Scholar
  8. Canadian Forest Service: 1992, Development and Structure of the Canadian Forest Fire Behaviour Prediction System, Canadian Forest Service, Information Report ST-X-3, Ottawa, ONT., 63 p.Google Scholar
  9. Ceccato, P., Flasse, S., Tarntola, S., Jacquemoud, S., Grégoire, J. M. 2001Detecting vegetation leaf water content using reflectance in the optical domainRemote Sen. Env772233CrossRefGoogle Scholar
  10. Chuvieco, E., Martin, M. P. 1994Global fire mapping and fire danger estimation using AVHRR imagesPhotogram. Eng. Remote Sens60(5)563570Google Scholar
  11. Chuvieco, E., Salas, F.J., Carvacho, L., Rodirguez-Silva, F. 1999aIntegrated fire risk mappingChuvieco, E. eds. Remote Sensing of Large Wildfires in the European Mediterranean BasinSpringer-VerlagBerlin6184Google Scholar
  12. Chuvieco, E., Deshayes, M., Stach, N., Cocero, D., and Riaño, D.: 1999b, Short-term fire risk: foliage moisture content estimation from satellite data. In: E. Chuvieco (Ed.), Remote Sensing of Large Wildfires in the European Mediterranean Basin Springer-Verlag, Berlin, pp. 17–38.Google Scholar
  13. Chuvieco, E., Aguado, I., Cocero, D., Riaño, D. 2003Design of an empirical index to estimate fuel moisture content from NOAA-AVHRR analysis in forest fire danger studiesInt. J. Remote Sens24(8)16211637Google Scholar
  14. Deblonde, G., Cihlar, J. 1993A multiyear analysis of the relationsip between surface environmental variables and NDVI over the Canadian landmassRemote Sens. Rev7151177Google Scholar
  15. Desbois, N., Vidal, A. 1995La télédétection dans la prévision des incendies de forêtIngénieries- EAT12129Google Scholar
  16. Desbois, N., Vidal, A. 1996Real-time monitoring of vegetation flammability using NOAA-AVHRR thermal infrared dataEARSeL Adv. Remote Sens4(4)2532Google Scholar
  17. Dominguez, L., Lee, B.S., Chuvieco, E. and Cihlar, J.: 1994, Fire danger estimation using AVHRR images in the Prairie provinces of Canada. In: Proc. 2nd Int. Conf. on Forest Fire Research, Coimbra, Portugal, 2(17), 679–690.Google Scholar
  18. Duchemin, B., Guyon, D., Lagouarde, J. P. 1999Potential and limits of NOAA-AVHRR temporal composite data for phenology and water stress monitoring of temperate forest ecosystemsInt. J. Remote. Sens20(5)895917CrossRefGoogle Scholar
  19. Gouyet, J. F., King, C., Le Gleau, H., Malon, J. F., Phulpin, T., and Valette, J. C.: 1991, Apport des données satellitaires NOAA-AVHRR dans le suivi de la végétation forestière, In: Proc. 5th Int. Coll. on Physical Measurements and Signatures in Remote Sensing, Courchevel, France, pp. 625–629.Google Scholar
  20. Goward, S. N., Waring, R. H., Dye, D. G., Yang, J. 1994Ecological remote sensing of OTTER satellite macroscale observationsEcol. Appl4(2)322343Google Scholar
  21. Granger, R. J.: 1997, Comparison of surface and satellite-derived estimates of evapotranspiration using a feedback algorithm, In: Proc. 3rd Int. Workshop on Application of Remote Sensing in Hydrology, Greenbelt, Maryland, pp. 71–81.Google Scholar
  22. Hardy, C. C., Burgan, R. E. 1999Evaluation of NDVI for monitoring live moisture in three vegetation types of the Western U.S.Photogram. Eng. Remote Sens65603610Google Scholar
  23. Illera, P., Fernandez, A., Delgado, J. A. 1996Temporal evolution of the NDVI as an indicator of forest fire dangerInt. J. Remote. Sens17(6)10931105Google Scholar
  24. Kogan, F. N. 2001Operational space technology for global vegetation assessmentBull. Am. Meteo. Soc82(9)19491964CrossRefGoogle Scholar
  25. Leblon, B. 2001Forest wildfire hazard monitoring using remote sensingRemote Sens. Rev20(1)143Google Scholar
  26. Leblon, B., Chen, J., Alexander, M., White, E.S. 2001Fire danger monitoring using NOAA-AVHRR NDVI images in the case of northern boreal forests, IntJ. Remote Sens2228392846CrossRefGoogle Scholar
  27. Leblon, B., Kaschike, E., Alexander, S., Doyle, M.E., Abbott, M.M. 2002Fire danger monitoring using ERS-1 SAR images over northern boreal forestsNat Hazards27231255CrossRefGoogle Scholar
  28. Lopez, S., Gonzalez, F., Llop, R., Cuevas, J. M. 1991An evaluation of the utility of NOAA-AVHRR images for monitoring forest fire risk in SpainInt. J. Remote. Sens12(9)18411851Google Scholar
  29. Moran, M.S., Vidal, A., Troufleau, D., Qi, J., Clarke, T. R., Pinter, P. J.,Jr., Mitchell, T.A., Inoue, Y., Neale, C. M. U. 1997Combining multifrequency microwave and optical data for crop management Remote SensEnviron.6196109Google Scholar
  30. Nemani, R. R., Running, S. W. 1989Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR dataJ. Appl. Meteo28(4)276284CrossRefGoogle Scholar
  31. Olioso, A., Chauki, H., Courault, D., Wigneron, J. P. 1999Estimation of evapotranspiration and photosynthesis by assimilation of remote sensing data into SVAT modelsRemote Sens. Environ68341356CrossRefGoogle Scholar
  32. Paltridge, G. W., Barber, J. 1988Monitoring grassland dryness and fire potential in Australia with NOAA-AVHRR dataRemote Sens. Environ25381394CrossRefGoogle Scholar
  33. Pierce, L. L., Running, S. W., Riggs, G. A. 1990Remote detection of canopy water stress in coniferous forests using the NS001 Thematic Mapper Simulator and the Thermal Infrared Multispectral ScannerPhotogram. Eng. Remote Sens56(5)579586Google Scholar
  34. Pinol, J., Filella, I., Ogaya, R., Penuelas, J. 1998Ground-based spectroradiometric estimation of live fine fuel moisture of Mediterranean plantsAgri. For. Meteo90173186CrossRefGoogle Scholar
  35. Prosper-Laget, V., Douguedroit, A., and Guinot, J. P.: 1994, A satellite index of forest fire occurence risk in summer in the Mediterranean area, In: Proc. 2nd Int. Conf. on Forest Fire Research, Coimbra, Portugal, Vol. 2, pp. 637–646.Google Scholar
  36. Prosper-Laget, V., Wigneron, J. P., Guinot, J. P., Seguin, B. 1995Utilisation du satellite NOAA pour la détection des risques d’incendies de forêtsLa Météorologie8(10)2838Google Scholar
  37. Saatchi, S.S., Zyl, J., Asrar, G. 1995Estimation of canopy water content in Konza Prairie grasslands using synthetic aperture radar measurements during FIFEJ. Geophys. Res100(D12)2548125496Google Scholar
  38. Strickland, G., Leblon, B., Gallant, L., and Alexander, M. E.: 2001, Monitoring fire danger of northern boreal forests from optical and thermal infrared NOAA-AVHRR images, In: Proc. 23th Can. Remote Sens. Symp., Ste-Foy, Canada, pp. 667–676.Google Scholar
  39. Teillet, P. M., Dudelzak, A. E., Pultz, T. J., McNairn, H., and Chichagov, A.: 2001, A framework for in-situ sensor measurement assimilation in remote sensing applications, In: Proc. 23th Can. Remote Sens. Symp., Ste-Foy, Canada, pp. 111–118Google Scholar
  40. Ustin, S., Roberts, D. A., Pinzon, J., Jacquemoud, S., Gardner, M., Scheer, G., Castaneda, C. M., Palacios-Orueta, A. 1998Estimating canopy water content of chaparral shrubs using optical methodsRemote Sens. Environ65280291Google Scholar
  41. Vidal, A., Devaux-Ros, C. 1995Evaluating forest fire hazard with a Landsat TM derived water stress indexAgric. For. Meteo77207224Google Scholar
  42. Vidal, A., Pinglo, F., Durand, H., Devaux-Ros, C., Maillet, A. 1994Evaluation of a temporal fire risk index in Mediterranean forests from NOAA thermal IRRemote Sens. Environ49296303Google Scholar

Copyright information

© Springer 2005

Authors and Affiliations

  1. 1.Remote Sensing and GIS Research Group, Faculty of Forestry and Environment ManagementUniversity of New BrunswickFrederictonCanada

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