Abstract
Satellite remote sensing has become a primary data source for fire danger rating prediction, fuel and fire mapping, fire monitoring, and fire ecology research. This paper summarizes the research achievements in these research fields, and discusses the future trend in the use of satellite remote-sensing techniques in wildfire management. Fuel-type maps from remote-sensing data can now be produced at spatial and temporal scales quite adequate for operational fire management applications. US National Oceanic and Atmospheric Administration (NOAA) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellites are being used for fire detection worldwide due to their high temporal resolution and ability to detect fires in remote regions. Results can be quickly presented on many Websites providing a valuable service readily available to fire agency. As cost-effective tools, satellite remote-sensing techniques play an important role in fire mapping. Improved remote-sensing techniques have the potential to date older fire scars and provide estimates of burn severity. Satellite remote sensing is well suited to assessing the extent of biomass burning, a prerequisite for estimating emissions at regional and global scales, which are needed for better understanding the effects of fire on climate change. The types of satellites used in fire research are also discussed in the paper. Suggestions on what remote-sensing efforts should be completed in China to modernize fire management technology in this country are given.
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References
Agee, J.K., and Pickford, S.G. 1985. Vegetation and fuel mapping of North Cascades National Park [R]. College of Forest Resources, University of Washington, Seattle. Final Report.
Albini, F.A. 1976. Estimating wildfire behavior and effects [R]. USDA For. Serv. Gen. Tech. Rep. INT-30.
Amiro, B., Todd, J., Wotton, B., Logan, K., Flannigan, M., Stocks, B., Mason, J., Martell, D., and Hirsch, K. 2001. Direct carbon emissions from Canadian forest fires, 1959–1999 [J]. Can. J. For. Res.,31: 512–525.
Amiro, B.D., Chen, J.M. 2003. Forest-fire-scar aging using SPOT-VEGETATION for Canadian ecoregions [J]. Can. J. For. Res.,33: 1116–1125.
Andreae, M.O. and Merlet, P. 2001. Emission of trace gases and aerosols from biomass burning [J]. Global Biogeochemical Cycles,15, (4): 955–966.
Andreae, M.O., Fishman, J., Garstang, M., Goldammer, J.G., Justice, C.O., Levine, J.S., Scholes, R.J., Stocks, B.J. and Thompson, A.M. 1994. Biomass burning in the global environment: first results from the IGAC/BIBEX Field Campaign STARE/TRACE-A/SAFARI-92 [C]. In: Prinn R. (Ed.) Global Atmospheric-Biospheric Chemistry. New York: Plenum Press, pp. 83–101.
Andrews, P.L. 1986. BEHAVE: fire behavior prediction and fuel modeling system. Burn subsystem. Part 1 [R]. USDA For. Serv. Gen. Tech. Rep. INT-194.
Bobbe, T., Lachowski, H., Maus, P., Greer, J., and Dull, C. 2001. A primer on mapping vegetation using remote sensing [J]. Internat. J. Wildl. Fire10: 277–287.
Brandis, K. and Jacobson, C. 2003. Estimation of vegetative fuel loads using Landsat TM imagery in New South Wales, Australia [J]. Internat. J. Wildl. Fire,12: 185–194.
Burgan, R.E., Klaver, R.W., and Klaver, J.M. 1998. Fuel Models and Fire Potential from Satellite and Surface Observations [J]. Int. J. Wild. Fire,8: 159–170.
Cahoon, D.R., Levine, J.S., Cofer III, W.R., and Stocks, B.J. 1994. The extent of burning in African savannas [J]. Adv. Space Res.14: 447–454.
Cahoon, D.R., Stocks, B.J., Levine, J.S., Cofer III, W.R., and Chung, C.C. 1992. Evaluation of a technique for satellite-derived estimation of biomass burning [J]. J. Geophys. Res.,97(D4): 3805–3814.
Castro, R., and Chuvieco, E. 1998. Modeling forest fire danger from geographic information systems [J]. Geocarto Int.13: 15–23.
Chuvieco, E., Riano, D., Aguado, I., and Cocero, D. 2002. Estimation of fuel moisture content from multitemporal analysis of Landsat Thematic Mapper reflectance data: applications in fire danger assessment [J]. Int. J. Remote Sensing,23: 2145–2162.
Crutzen, P.J. and Andreae, M.O. 1990. Biomass burning in the tropics: impact on atmospheric chemistry and biogeochemical cycles. [J] Science.250: 1669–1678.
Crutzen, P.J., Heidt, L.E., Krasnec, J.P., Pollock, W.H., and Seiler, W. 1979. Biomass burning as a source of atmospheric gases: CO, H2, N2O, NO, CH3Cl, and COS [J]. Nature,282: 253–257.
Deeming, J.E., Burgan, R.E., and Cohen, J.D. 1978. The national fire-danger rating system—1978 [R]. USDA For. Serv. Gen. Tech. Rep. INT-39.
Dickinson, R.E., 1993. Effect of fires on global radiation budget through aerosol and cloud properties [C]. In: P.J. Crutzen and J.G. Goldammer (eds.) Fire in the Environment: The Ecological, Atmospheric, and Climatic Importance of Vegetation Fires New York: John Wiley & Sons, pp. 107–122
Dixon, R., Shipley, R., and Briggs, A. 1984. Landsat—a tool for mapping fuel types in the boreal forest of Manitoba: A pilot study [R]. Manitoba Remote Sensing Center, Fire Management and Communications Section, Canada Centre for Remote Sensing, Winnipeg, Man.
Dozier, J. 1981. A method for satellite identification of surface temperature fields of subpixel resolution [J]. Remote Sens. Environ.,11: 221–229.
FAO. 1986. Wildland Fire Management Terminology. Forestry Pap. M-99.
Finney, M.A. and Andrews, P.L. 1994. The FARSITE fire area simulator: fire management applications and lessons of summer 1994.in Presented at the Interior West Fire Council Meeting and Symposium: Coeur d'Alene, ID, Nov. 1–2, 1994.
Flannigan, M.D. 1985. Forest Fire Monitoring Using the NOAA Satellite Series, M.S. Thesis Department of Atmospheric Sciences, Colorado State Univ., Fort Collins, CO.
Flannigan, M.D. and Vonder Haar, T.H. 1986. Forest fire monitoring using NOAA satellite AVHRR [J]. Can. J For. Res.,16: 975–982.
Forestry Canada Fire Danger Group. 1992. Development and structure of the Canadian Forest Fire Behavior Prediction System [R]. Forestry Canada, Ottawa, ON. Information Report ST-X-3.
Fraser, R.H., Li, Z., and Cihlar, J. 2000. Hotspot and NDVI differencing synergy (HANDS): a new technique for burned area mapping over boreal forest [J]. Remote Sens. Environ.,74: 362–376.
Fraser, R.H., and Li, Z. 2002. Estimating fire related parameters in boreal forest using SPOT VEGETATION [J]. Remote Sens. Environ.,82: 95–110.
Houghton, J.T., Meira Fihno, L.G., Hoesung, L., Callander, B.A., Haites, E., Harris, N., and Maskell, K. 1995. Climate Change 1994 [R]. Cambridge: IPCC Cambridge University Press.
Illera, P., Fernandez, A., Calle, A., and Casanova, J.L., 1996. Temporal evolution of the NDVI as an indicator of forest fire danger [J]. Internat. J. Remote Sens.,17: 1093–1105.
Justice, C.O., Kendall, J.D., Dowry, RR., and Scholes, R.J. 1996. Satellite remote sensing of fires during the SAFARI campaign using NOAA advanced very high resolution radiometer data [J]. J. Geophy., Res.,101: 23,851.
Kaufman, Y.J., Setzer, A., Ward, D., Tanre, D., Holben, B.N., Menzel, P., Pereira, M.C., and Rasmussen, R. 1992. Biomass burning airborne and spaceborne experiment in the Amazonas (BASE-A) [J]. J. Geophys. Res.,97: 14581–14599.
Kaufman, Y.J., Tucker, C.J., and Fung, I. 1990b. Remote Sensing of Biomass Burning in the Tropics [J]. J. Geophv. Res.,95(D7): 9927–9939.
Kaufman, Y.J. and Nakajima, T. 1993. Effect of Amazon smoke on cloud microphysics and albedo-analysis from satellite imagery [J]. J. Applied Meteorology,32: 729–744.
Kaufman, Y.Z., Setzer, A., Justice, C., Tucker, C.J., Pereira, M.C., and Fung, I. 1990a. Remote sensing of Biomass Burning in the Tropics [C]. In: J.G. Goldammer (ed.) Fire in the Tropical Biota: Ecosystem Processes and Global challenges. Berlin: Springer-Verlag, pp. 371–399.
Keane, R.E., Burgan, R., and Wagtendonk, J.V. 2001. Mapping wildland fuels for fire management across multiple scales: Integrating remote sensing, GIS, and biophysical modeling [J]. Int. J. Wild. Fire,10: 301–319.
Konzelmann, T., Cahoon, D.R., and Whitlock, C.H. 1996. Impact of biomass burning in equatorial Africa on the downward surface shortwave irradiance: Observations versus calculations [J]. J. Geophys. Res.,101(D17): 2833–2844.
Kourtz, P.H. 1977. An application of Landsat digital technology to forest fire fuel type mapping [C].In: Proceedings of the 11th International Symposium on Remote Sensing of the Environment, Ann Arbor, Mich. Environmental Research Institute of Michigan, Ann Arbor, Mich., pp. 1111–1115.
Kwasny, J.L. 2000. Mapping vegetation in green swamp preserve for fuel modeling using remote sensing techniques. Nicholas School of the Environment of Duke University Great Britain. Master's thesis.
Langaas, S. and Muirhead, K. 1988. Monitoring bushfires in West Africa by weather satellites. In: The 22nd International Symposium on Remote Sensing of the Environment, October 20–26, Abidjan, Cote d. Ivoire.
Lawson, B.D., Stocks, B.J., Alexander, M.E., and Van Wagner, C.E. 1985. A system for predicting fire in Canadian forests [C]. In: Proceedings of the 8th Conference on Fire and Forest Meteorology, Detroit. Mich. Society of American Foresters, Bethesda, Md.
Lee, T.F. and Tag, P.M. 1990. Improved Detection of Hotspots using the AVHRR 3.7 um Channel [J]. Bull. Amer. Meteorol. Soc.,71: 1722–1730.
Li, Z., Frsaser, R., Jin, J., Abuelgasim, A.A., Csiszar, I., Gong, P., Pu, R. and Hao, W., 2003. Evaluation of algorithms for fire detection and mapping across North America, from satellite [J]. J. Geophys. Res.,108(D2): 4076.
Li, Z., Kaufman, Y.J., Ichoku, C., Fraser, R., Trishchenko, A., Giglio, L., Jin, J., and Yu, X. 2000. A review of AVHRR-based active fire detection algorithms: principles, limitations, and recommendations [R]. Canada Cent. Remote Sens., Ottawa, Canada.
Lim, R. and Bretschneider, T. 2004. Autonomous monitoring of fire-related haze from space [C]. In: Proceedings of the International Conference on Imaging Science, Systems, and Technology, pp. 101–105.
Lopez, A.S., Ayanz, J.S., and Burgan, R.E. 2002. Integration of satellite sensor data, fuel type maps and meteorological observations for evaluation of forest fire risk at the pan-European scale [J]. Int. J. Remote Sens.,23: 2713–2719.
Lopez, S., Gonzalez-Alonso, F., Llop, R., and Cuevas, J.M., 1991. An evaluation of the utility of NOAA-AVHRR images for monitoring forest fires risk in Spain. Internat. J. Remote Sens.12: 1841–1851.
Matson, M. and Holben, B. 1987. Satellite detection of tropical burning in Brazil [J]. Int. J. Remote Sens.,8: 509–516.
Menzel, W.P. and Prins, E.M. 1996. Monitoring biomass burning with the new generation of geostationary satellites [C]. In: Change, J.S. Levine (Ed.) Biomass Burning and Global. Cambridge MA: The MIT Press.
Meritxell, G., and San-Miguel-Ayanz, J. 2003. Fire scar detection in Central Portugal Using RADARSAT-1 and ERS-2 SAR Data. Available at:http://natural-hazards.jrc.it/documents/fires/2003-publications/igarss-paper.pdf
Merrill, D.F. and Alexander, M.E. 1987. Glossary of forest fire management terms [R]. National Research Council of Canada, Committee for Forest Fire Management, Ottawa, Ont.
Oswald, B.P., Fancher, J.T., Kulhavy, D.L., and Reeves, H.C. 1999. Classifying fuels with aerial photography in East Texas [J]. Int. J. Wildland Fire,9: 109–113.
Paltridge, G.W. and Barber, J. 1988. Monitoring grasslands dryness and fire potential in Australia with NOAA/AVHRR data [J]. Remote Sens. Environ.,25: 381–394.
Penner, J.E., Dickenson R.E., and O.Neill, C.A. 1992. Effects of aerosol from biomass burning on the global radiation budget [J]. Science,256: 1432–1434.
Prins, E.M. and Menzel, W.P. 1992. Geostationary satellite detection of biomass burning in South America [J]. Int. T. Remote Sens.,13: 2783–2799.
Prins, E.M. and Menzel, W.P. 1994. Trends in South American biomass burning detected with the GOES visible infrared spin scan radiometer atmospheric sounder from 1983 to 1991 [J]. J. Geoph. Res.,99: 16719–16735.
Prins, E.M. and Menzel, W.P. 1996. Investigation of biomass burning and aerosol loading and transport utilizing geostationary satellite data [C]. In: J.S. Levine (Ed.) Biomass Burning and Global Change. Cambridge MA: The MIT Press.
Remmel, T.K. and Perera, A.H. 2001. Fire mapping in a northern boreal forest: assessing AVHRR/NDVI methods of change detection [M]. Forest Ecology and Management,152: 119–129.
Riaño, D., Chuvieco, E., Salas, J., Orueta, A.P., and Bastarrika, A. 2002. Generation of fuel type maps from Landsat TM images and ancillary data in Mediterranean ecosystems [J]. Can. J. For. Res.,32: 1301–1315.
Roberts, D.A., Green, R.O., and Adams, J.B. 1997. Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS [J]. Remote Sens. Environ.,62: 223–240.
Ruecker, G. and Siegert, F. 2000. Burn scar mapping and fire damage assessment using ERS-2 Sar images in East Kalimantan, Indonesia [R]. IAPRS. Vol. XXXIII, Amsterdam, 1–8.
Salomonson, V.V., Barnes, W.L., Maymon, P.W., Montgomery, H.E., and Ostrow, H. 1989. MODIS: Advanced Facility Instrument for Studies of the Earth as a System [J]. IEEE Trans. on Geosci. and Remote Sens.,27: 145–153.
Setzer, A.W., and Verstraete, M.M. 1994. Fire and glint in AVHRR Channel 3: A possible reason for the non-saturation mystery [J]. Int. J. of Remote Sens.,15: 711–718.
Soja, A.J., Cofer, W.R., Shugart, H.H., Sukhinin, A.I., Stackhouse Jr., P.W., McRae, D.J., and Conard, s.G. 2004. Estimating fire emissions and disparities in boreal Siberia (1998–2002) [J]. J. Geophys. Res.,109: D14S06.
Stephens, G. and Matson, M., 1989. Fire Detection Using the NOAA-N Satellites [C]. In: Proceedings of the 10th Conference on Fire and Forest Meteology, April 17–21, Ottawa, Canada.
Steven, P.B., Koch, S.W., and Hansen, L.A. 2002. Evolutionary computation and post-wildfire land-cover mapping with multispectral imagery. Available at:http://www.genie.lanl.gov/green/publications/brumbySPIE4545.pdf
Stocks, B.J., Lee, B.S., and Martell, D.L. 1996. Some potential carbon budget implications of fire management in the boreal forest [C]. pp. 89–96 In: M.J. Apps and D.T. Price (Eds.) Forest Ecosystems. Forest Management, and the Global Carbon Cycle. NATO ASI Series. Berlin: Springer-Verlag.
Vidal, A., Pinglo, F., Durand, H., Devaux-Ros, C., and Maillet, A. 1994. Evaluation of temporal fire risk index in the Mediterranean forest from NOAA thermal IR [J]. Remote Sens. Environ.,49: 296–303.
Viegas, X., Bovio, G., Ferreira, A., Nosenzo, A., and Sol, B. 2000. Comparative study of various methods of fire danger evaluation in southern Europe [J]. Internat. J. Wildl. Fire,9: 235–246.
Wild, M. 1999. Discrepancies between model-calculated and observed short-wave atmospheric absorption in areas with high aerosol loadings [J]. J. Geophys. Res.,104: 27,361–27,371.
Wulf, D.E., Goossens, R.E., Deroover, B.P., and Borry, F.C. 1990. Extraction of forest stand parameters from panchromatic and multispectral SPOT-1 data [J]. Int. J. Remote Sens.,11: 1571–1588.
Zhu, Z., and Evans, D.L. 1994. U.S. forest types and predicted percent forest cover from AVHRR data [J]. Photogramm. Eng. Remote Sens.60: 525–531.
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Foundation Item: This paper was supported by the National Science Foundation of Beijing (No. 6042025), China NKBRSF Project (No. 2001CB409600) and the fund of Forest Protection Laboratory, State Forestry Administration.
Biography: TIAN Xiao-rui (1971-), Corresponding author, male, Ph. Doctor, associate professor in Research Institute of Forestry Protection, Chinese Academy of Forestry, Beijing 100091, P.R. China.
Responsible editor: Chai Ruihai
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Xiao-rui, T., Mcrae, D.J., Li-fu, S. et al. Satellite remote-sensing technologies used in forest fire management. Journal of Forestry Research 16, 73–78 (2005). https://doi.org/10.1007/BF02856861
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DOI: https://doi.org/10.1007/BF02856861