Satellite remote-sensing technologies used in forest fire management

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.

Keywords

Satellite remote sensing / Fire management / Fuel mapping / Fire detection / Review / S762 / A

References

[1] Agee J.K., Pickford S.G. Vegetation and fuel mapping of North Cascades National Park [R], 1985 Seattle: College of Forest Resources, University of Washington

[2] Albini, F.A. 1976. Estimating wildfire behavior and effects [R]. USDA For. Serv. Gen. Tech. Rep. INT-30.

[3] Amiro B., Todd J., Wotton B., Logan K., Flannigan M., Stocks B., Mason J., Martell D., Hirsch K. Direct carbon emissions from Canadian forest fires, 1959–1999 [J]. Can. J. For. Res., 2001, 31: 512-525.

[4] Amiro B.D., Chen J.M. Forest-fire-scar aging using SPOT-VEGETATION for Canadian ecoregions [J]. Can. J. For. Res., 2003, 33: 1116-1125.

[5] Andreae M.O., Merlet P. Emission of trace gases and aerosols from biomass burning [J]. Global Biogeochemical Cycles, 2001, 15(4): 955-966.

[6] Andreae M.O., Fishman J., Garstang M., Goldammer J.G., Justice C.O., Levine J.S., Scholes R.J., Stocks B.J., Thompson A.M. Prinn R. Biomass burning in the global environment: first results from the IGAC/BIBEX Field Campaign STARE/TRACE-A/SAFARI-92 [C] Global Atmospheric-Biospheric Chemistry, 1994 Harbin: Plenum Press 83-101.

[7] 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.

[8] Bobbe T., Lachowski H., Maus P., Greer J., Dull C. A primer on mapping vegetation using remote sensing [J]. Internat. J. Wildl. Fire, 2001, 10: 277-287.

[9] Brandis K., Jacobson C. Estimation of vegetative fuel loads using Landsat TM imagery in New South Wales, Australia [J]. Internat. J. Wildl. Fire, 2003, 12: 185-194.

[10] Burgan R.E., Klaver R.W., Klaver J.M. Fuel Models and Fire Potential from Satellite and Surface Observations [J]. Int. J. Wild. Fire, 1998, 8: 159-170.

[11] Cahoon D.R., Levine J.S., Cofer W.R., Stocks B.J. The extent of burning in African savannas [J]. Adv. Space Res., 1994, 14: 447-454.

[12] Cahoon D.R., Stocks B.J., Levine J.S., Cofer W.R., Chung C.C. Evaluation of a technique for satellite-derived estimation of biomass burning [J]. J. Geophys. Res., 1992, 97(D4): 3805-3814.

[13] Castro R., Chuvieco E. Modeling forest fire danger from geographic information systems [J]. Geocarto Int., 1998, 13: 15-23.

[14] Chuvieco E., Riano D., Aguado I., Cocero D. Estimation of fuel moisture content from multitemporal analysis of Landsat Thematic Mapper reflectance data: applications in fire danger assessment [J]. Int. J. Remote Sensing, 2002, 23: 2145-2162.

[15] Crutzen P.J., Andreae M.O. Biomass burning in the tropics: impact on atmospheric chemistry and biogeochemical cycles. [J]. Science., 1990, 250: 1669-1678.

[16] Crutzen P.J., Heidt L.E., Krasnec J.P., Pollock W.H., Seiler W. Biomass burning as a source of atmospheric gases: CO, H₂, N₂O, NO, CH₃Cl, and COS [J]. Nature, 1979, 282: 253-257.

[17] 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.

[18] Dickinson R.E. Crutzen P.J., Goldammer J.G. Effect of fires on global radiation budget through aerosol and cloud properties [C] Fire in the Environment: The Ecological, Atmospheric, and Climatic Importance of Vegetation Fires, 1993 Harbin: John Wiley & Sons 107-122.

[19] Dixon R., Shipley R., Briggs A. Landsat—a tool for mapping fuel types in the boreal forest of Manitoba: A pilot study [R], 1984 Winnipeg, Man: Manitoba Remote Sensing Center, Fire Management and Communications Section, Canada Centre for Remote Sensing

[20] Dozier J. A method for satellite identification of surface temperature fields of subpixel resolution [J]. Remote Sens. Environ., 1981, 11: 221-229.

[21] FAO. 1986. Wildland Fire Management Terminology. Forestry Pap. M-99.

[22] 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.

[23] Flannigan M.D. Forest Fire Monitoring Using the NOAA Satellite Series, M.S. Thesis, 1985 Fort Collins, CO: Department of Atmospheric Sciences, Colorado State Univ.

[24] Flannigan M.D., Vonder Haar T.H. Forest fire monitoring using NOAA satellite AVHRR [J]. Can. J For. Res., 1986, 16: 975-982.

[25] 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.

[26] Fraser R.H., Li Z., Cihlar J. Hotspot and NDVI differencing synergy (HANDS): a new technique for burned area mapping over boreal forest [J]. Remote Sens. Environ., 2000, 74: 362-376.

[27] Fraser R.H., Li Z. Estimating fire related parameters in boreal forest using SPOT VEGETATION [J]. Remote Sens. Environ., 2002, 82: 95-110.

[28] Houghton J.T., Meira Fihno L.G., Hoesung L., Callander B.A., Haites E., Harris N., Maskell K. Climate Change 1994 [R], 1995 Cambridge: IPCC Cambridge University Press

[29] Illera P., Fernandez A., Calle A., Casanova J.L. Temporal evolution of the NDVI as an indicator of forest fire danger [J]. Internat. J. Remote Sens., 1996, 17: 1093-1105.

[30] Justice C.O., Kendall J.D., Dowry RR., Scholes R.J. Satellite remote sensing of fires during the SAFARI campaign using NOAA advanced very high resolution radiometer data [J]. J. Geophy., Res., 1996, 101: 23,851-23,851.

[31] Kaufman Y.J., Setzer A., Ward D., Tanre D., Holben B.N., Menzel P., Pereira M.C., Rasmussen R. Biomass burning airborne and spaceborne experiment in the Amazonas (BASE-A) [J]. J. Geophys. Res., 1992, 97: 14581-14599.

[32] Kaufman Y.J., Tucker C.J., Fung I. Remote Sensing of Biomass Burning in the Tropics [J]. J. Geophv. Res., 1990, 95(D7): 9927-9939.

[33] Kaufman Y.J., Nakajima T. Effect of Amazon smoke on cloud microphysics and albedo-analysis from satellite imagery [J]. J. Applied Meteorology, 1993, 32: 729-744.

[34] Kaufman Y.Z., Setzer A., Justice C., Tucker C.J., Pereira M.C., Fung I. Goldammer J.G. Remote sensing of Biomass Burning in the Tropics [C] Fire in the Tropical Biota: Ecosystem Processes and Global challenges, 1990 Berlin: Northeast Forestry University and Ecological Society of China 371-399.

[35] Keane R.E., Burgan R., Wagtendonk J.V. Mapping wildland fuels for fire management across multiple scales: Integrating remote sensing, GIS, and biophysical modeling [J]. Int. J. Wild. Fire, 2001, 10: 301-319.

[36] Konzelmann T., Cahoon D.R., Whitlock C.H. Impact of biomass burning in equatorial Africa on the downward surface shortwave irradiance: Observations versus calculations [J]. J. Geophys. Res., 1996, 101(D17): 2833-2844.

[37] Kourtz P.H. An application of Landsat digital technology to forest fire fuel type mapping [C] Proceedings of the 11th International Symposium on Remote Sensing of the Environment, Ann Arbor, Mich, 1977 Ann Arbor, Mich.: Environmental Research Institute of Michigan 1111-1115.

[38] 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.

[39] 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.

[40] Lawson B.D., Stocks B.J., Alexander M.E., Van Wagner C.E. A system for predicting fire in Canadian forests [C] Proceedings of the 8th Conference on Fire and Forest Meteorology, Detroit. Mich, 1985 Bethesda, Md: Society of American Foresters

[41] Lee T.F., Tag P.M. Improved Detection of Hotspots using the AVHRR 3.7 um Channel [J]. Bull. Amer. Meteorol. Soc., 1990, 71: 1722-1730.

[42] Li Z., Frsaser R., Jin J., Abuelgasim A.A., Csiszar I., Gong P., Pu R., Hao W. Evaluation of algorithms for fire detection and mapping across North America, from satellite [J]. J. Geophys. Res., 2003, 108(D2): 4076-4076.

[43] Li Z., Kaufman Y.J., Ichoku C., Fraser R., Trishchenko A., Giglio L., Jin J., Yu X. A review of AVHRR-based active fire detection algorithms: principles, limitations, and recommendations [R], 2000 Ottawa, Canada: Canada Cent. Remote Sens.

[44] 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.

[45] Lopez A.S., Ayanz J.S., Burgan R.E. 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., 2002, 23: 2713-2719.

[46] Lopez S., Gonzalez-Alonso F., Llop R., Cuevas J.M. An evaluation of the utility of NOAA-AVHRR images for monitoring forest fires risk in Spain Internat. J. Remote Sens., 1991, 12: 1841-1851.

[47] Matson M., Holben B. Satellite detection of tropical burning in Brazil [J]. Int. J. Remote Sens., 1987, 8: 509-516.

[48] Menzel W.P., Prins E.M. Change J.S. Levine Monitoring biomass burning with the new generation of geostationary satellites [C] Biomass Burning and Global, 1996 Cambridge MA: The MIT Press

[49] 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

[50] Merrill D.F., Alexander M.E. Glossary of forest fire management terms [R], 1987 Ottawa, Ont: National Research Council of Canada, Committee for Forest Fire Management

[51] Oswald B.P., Fancher J.T., Kulhavy D.L., Reeves H.C. Classifying fuels with aerial photography in East Texas [J]. Int. J. Wildland Fire, 1999, 9: 109-113.

[52] Paltridge G.W., Barber J. Monitoring grasslands dryness and fire potential in Australia with NOAA/AVHRR data [J]. Remote Sens. Environ., 1988, 25: 381-394.

[53] Penner J.E., Dickenson R.E., O.Neill C.A. Effects of aerosol from biomass burning on the global radiation budget [J]. Science, 1992, 256: 1432-1434.

[54] Prins E.M., Menzel W.P. Geostationary satellite detection of biomass burning in South America [J]. Int. T. Remote Sens., 1992, 13: 2783-2799.

[55] Prins E.M., Menzel W.P. 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., 1994, 99: 16719-16735.

[56] Prins E.M., Menzel W.P. Levine J.S. Investigation of biomass burning and aerosol loading and transport utilizing geostationary satellite data [C] Biomass Burning and Global Change, 1996 Cambridge MA: The MIT Press

[57] Remmel T.K., Perera A.H. Fire mapping in a northern boreal forest: assessing AVHRR/NDVI methods of change detection [M] Forest Ecology and Management, 2001, 152: 119-129.

[58] Riaño D., Chuvieco E., Salas J., Orueta A.P., Bastarrika A. Generation of fuel type maps from Landsat TM images and ancillary data in Mediterranean ecosystems [J]. Can. J. For. Res., 2002, 32: 1301-1315.

[59] Roberts D.A., Green R.O., Adams J.B. Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS [J]. Remote Sens. Environ., 1997, 62: 223-240.

[60] Ruecker G., Siegert F. Burn scar mapping and fire damage assessment using ERS-2 Sar images in East Kalimantan, Indonesia [R] IAPRS, 2000, XXXIII: 1-8.

[61] Salomonson V.V., Barnes W.L., Maymon P.W., Montgomery H.E., Ostrow H. MODIS: Advanced Facility Instrument for Studies of the Earth as a System [J]. IEEE Trans. on Geosci. and Remote Sens., 1989, 27: 145-153.

[62] Setzer A.W., Verstraete M.M. Fire and glint in AVHRR Channel 3: A possible reason for the non-saturation mystery [J]. Int. J. of Remote Sens., 1994, 15: 711-718.

[63] Soja A.J., Cofer W.R., Shugart H.H., Sukhinin A.I., Stackhouse P.W., McRae D.J., Conard s.G. Estimating fire emissions and disparities in boreal Siberia (1998–2002) [J]. J. Geophys. Res., 2004, 109: D14S06-D14S06.

[64] 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.

[65] 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

[66] Stocks B.J., Lee B.S., Martell D.L. Apps M.J., Price D.T. Some potential carbon budget implications of fire management in the boreal forest [C] Forest Ecosystems. Forest Management, and the Global Carbon Cycle, 1996 Berlin: Northeast Forestry University and Ecological Society of China 89-96.

[67] Vidal A., Pinglo F., Durand H., Devaux-Ros C., Maillet A. Evaluation of temporal fire risk index in the Mediterranean forest from NOAA thermal IR [J]. Remote Sens. Environ., 1994, 49: 296-303.

[68] Viegas X., Bovio G., Ferreira A., Nosenzo A., Sol B. Comparative study of various methods of fire danger evaluation in southern Europe [J]. Internat. J. Wildl. Fire, 2000, 9: 235-246.

[69] Wild M. Discrepancies between model-calculated and observed short-wave atmospheric absorption in areas with high aerosol loadings [J]. J. Geophys. Res., 1999, 104: 27,361-27,371.

[70] Wulf D.E., Goossens R.E., Deroover B.P., Borry F.C. Extraction of forest stand parameters from panchromatic and multispectral SPOT-1 data [J]. Int. J. Remote Sens., 1990, 11: 1571-1588.

[71] Zhu Z., Evans D.L. U.S. forest types and predicted percent forest cover from AVHRR data [J]. Photogramm. Eng. Remote Sens., 1994, 60: 525-531.