Forest fire risk zone mapping from satellite images and GIS for Baihe Forestry Bureau, Jilin, China

Abstract

A forest fire can be a real ecological disaster regardless of whether it is caused by natural forces or human activities, it is possible to map forest fire risk zones to minimize the frequency of fires, avert damage, etc. A method integrating remote sensing and GIS was developed and applied to forest fire risk zone mapping for Baihe forestry bureau in this paper. Satellite images were interpreted and classified to generate vegetation type layer and land use layers (roads, settlements and farmlands). Topographic layers (slope, aspect and altitude) were derived from DEM. The thematic and topographic information was analyzed by using ARC/INFO GIS software. Forest fire risk zones were delineated by assigning subjective weights to the classes of all the layers (vegetation type, slope, aspect, altitude and distance from roads, farmlands and settlements) according to their sensitivity to fire or their fire-inducing capability. Five categories of forest fire risk ranging from very high to very low were derived automatically. The mapping result of the study area was found to be in strong agreement with actual fire-affected sites.

Keywords

Forest fire risk / GIS / Remote sensing / Baihe forestry bureau / S762.31 / A

References

[1] Albini, F.A. 1976. Estimating wildfire behavior and effects [R]. USDA Forest Service General Technical Report INT-30. 23 pp.

[2] Atkinson P.M., Lewis P. Geostatistical classification for remote sensing: an introduction [J]. Computers & Geosciences, 2000, 26: 361-371.

[3] Botton S., Duquenne F. ‘GPS, location and navigation.’ [M], 1997 Paris, France: Edition Hermes

[4] Castro R., Chuvieco E. Modeling forest fire danger from Geographical Information Systems [J]. Geocarto International, 1998, 13: 15-24.

[5] Chou Y.H. Management of wildfires with a geographical information system [J]. International Journal of Geographical Information Systems, 1992, 6: 123-140.

[6] Chuvieco E., Congalton R.G. Application of remote sensing and geographic information systems to forest fire hazard mapping [J]. Remote Sensing of the Environment, 1989, 29: 147-159.

[7] Chuvieco E., Salas J. Mapping the spatial distribution of forest fire danger using GIS [J]. International Journal of Geographical Information Systems, 1996, 10: 333-345.

[8] George L.W., Ashley Perry D., Sparrow Ian F. Owens A GIS-supported model for the simulation of the spatial structure of wildland fire, Cass Basin, New Zealand [J]. Journal of Applied Ecology, 1999, 36(4): 502-518.

[9] Goodrick S., Jim B. Florida's fire management information system [C] Proceedings from the Joint Fire Science Conference and Workshop, 1999 Moscow, Idaho: University of Idaho 3-11.

[10] Gui Zhang, Feng Liu, Zhigao Yang Study of Guangzhou's forest fire hazardous areas based on RS and GIS [J]. Journal of Central South Forestry University, 2003, 23(4): 62-65. (in Chinese)

[11] Hansen M., Dubayah R., Defries R. Classification trees: an alternative to traditional land cover classifiers [J]. International Journal of Remote Sensing, 1996, 17(5): 1075-1081.

[12] Zhidong Hu Forest Fire Prevention, 2003 the 1st edition Beijing: China Forestry Publishing House

[13] Ilmavirta A. The use of GIS-system in catastrophe and emergency management in Finnish municipalities [J]. Computers, Environment and Urban Systems, 1995, 19: 171-178.

[14] Jaiswal R.K., Mukherjee S., Raju D.K. et al. Forest fire risk zone mapping from satellite imagery and GIS [J]. International Journal of Applied Earth Observation and Geoinformation, 2002, 4: 1-10.

[15] Keane, R.E., Garner, J.L., Schmidt, K.M.et al. 1998. Development of the Input Data Layers for the FARSITE Fire Growth Model for the Selway-Bitterroot Wilderness Complex, USA [R]. USDA Forest Service General Technical Report RMRS-GTR-3, Fort Collins.

[16] Keane, R.E., Mincemoyer, S.A., Schmidt, K.M.,et al. 2000. Mapping vegetation and fuels for fire management on the Gila National Forest Complex. New Mexico [R]. USDA Forest Service General Technical Report RMRS-GTR-46-CD, Fort Collins.

[17] Keramitsoglou I., Kiranoudis C.T., Sarimveis H. et al. A multidiseiplinary decision support system for forest fire crisis management [J]. Environmental Management, 2004, 33(2): 212-225.

[18] Lymberopoulos N., Papadopoulos C., Stefanakis L. et al. A GIS-based forest fire management information system [J]. EARSeL Advances in Remote Sensing, 1996, 4(4): 68-75.

[19] Mariel A., Marielle J. Wildland fire risk mapping using a geographic information system and including satellite data: Example of “Les Maures” forest, south east of France [J]. EARSeL Advances in Remote Sensing, 1996, 4(4): 49-56.

[20] Pew K. L., Larsen C.P.S. GIS analysis of spatial and temporal patterns of human-caused wildfires in the temperate rain forest of Vancouver Island, Canada [J]. Forest Ecology and Management, 2001, 140: 1-18.

[21] Román-Cuesta R.M., Gracia M., Javier R. Environmental and human factors influencing fire trends in ENSO and Non-ENSO years in tropical Mexico [J]. Ecological Applications, 2003, 13(4): 1177-1192.

[22] Rothermel, R.C. 1972. A mathematical model for predicting fire spread in wildland fuels [R]. USDA Forest Service Research Paper INT-115.

[23] Salas J., Chuvieco E. Geographic information systems for wildland fire risk mapping [J]. Wildfire, 1994, 3(2): 7-13.

[24] Sauvagnargues S., Dusserre G., Poppi J.C. et al. Geographical Information Systems applied to security services [J]. International Journal of GIS and Spatial Analysis, 1997, 7: 353-371.

[25] shao G., Zhao G. Protection versus harvest of old-growth forests on Changbai Mountain (China and North Korea): a remote sensing application [J]. Natural Areas Journal, 1998, 18: 334-341.

[26] Shao G., Zhao G., Zhao S. et al. Forest cover types derived from Landsat Thematic Mapper imagery for the Changbai Mountain area of China [J]. Canadian Journal of Forest Research, 1996, 26(2): 206-216.

[27] Jilin Tang, Xiaoli Zhang Study on the division of forest fire danger in the forestry bureau by using remote sensing and geographical information system [J]. Journal of Beijing Forestry University, 1996, 18: 13-21. (in Chinese)

[28] Vega-García C., Woodard P.M., Titus S.J. et al. A logit model for predicting the daily occurrence of human caused forest fires [J]. International Journal of Wildland Fire, 1995, 5: 101-111.

[29] Vélez Muñoz R. Incendios forestales y su relación con el medio rural [J]. Revista de Estudios Agro-Sociales, 1986, 136: 195-222.

[30] Zhengfei Wang Forest Meteorology [M], 1985 Beijing: China Forestry Publishing House

[31] Zhang P., Shao G., Zhao G. et al. Ecology: China's Forest Policy for the 21^st Century [J]. Science, 2000, 288(5474): 2135-2136.

[32] Huanneng Zheng, Shuren Yao Forest fire risk zone in China [J]. Forest Fire Prevention, 1993, 36: 14-16. (in Chinese)