Forest fire risk mapping using analytical hierarchy process technique and frequency ratio method (Case study: Sardasht Forests, NW Iran)

Document Type : Research article

Authors

1 M. Sc. Forestry, Department of Forestry, Faculty of Natural Resources, Urmia University, Urmia, ‎I.R. Iran

2 Assistant Prof., Department of Forestry, Faculty of Natural Resources, Urmia University, Urmia, ‎I.R. Iran

3 Assistant Prof., Department of Range and Watershed Management Engineering, Faculty of ‎Natural Resources, Urmia University, Urmia, I.R. Iran.‎

Abstract

This research aimed at mapping the risk of wildfire based on a number of influential factors including Elevation, slope, aspect, average annual precipitation, average maximum monthly temperature, land use/land cover, distance from road, distance from river, distance from agricultural lands and population density. The study was conducted in a study site encompassing 273.3 km2 near Sardasht in northwest Iran. The burned areas were initially mapped by field visits. Then, using Analytical Hierarchy Process (AHP) method, influence of each factor on occurrence of fire was compared pairwise and weights were assigned to them. The frequency ratio method was used to derive a weight for individual classes of each factor. This was followed by mapping fire risk zones based on weighted combination of digital maps of the influential factors. The zonation map was later divided in five risk classes (ranging from very high to very low) by Jenks method. Validation of the risk map indicated the 98.44 percent of the observed fires to be located in the mapped high risk zones. This represents the high accuracy of the applied technique for wildfire risk mapping across the study site.

Keywords

References

- Almeida, R. 1994. Forest fire risk areas and definition of the prevention priority planning actions using GIS. Ecological Modelling, 3(7): 1-9.
- Alonso, J.A. and Lamata, M.T. 2006. Consistency in the analytical hierarchy process: A new approach. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 14(4): 445-459.
- Anonymous, 2013. Sardasht Forest Management Plan. Administration of Natural Resources at West Azerbaijan, 87p (In Persian).
- Beygi Heidarlou, H., Banj Shafiei, A. and Erfanian, M. 2013. Assess of important environmental and physiographic factorsin occurrence of Forest Fires in Sardasht.Abstract of the1st Scientific and Technical Conference of Rural development and agriculture with emphasis on national production, Piranshahr, 14 Mar. 2013: 10p.
- Burgess, R. 2011. Development of a spatial, dynamic, fuzzy fire risk model for Chitwan District, Nepal. M.Sc. thesis, Faculty of Geo-Information Science and Earth Observation, University of Twente, 96p.
- Chavan, M.E., Das, K.K. and Suryawanshi, R.S. 2012. Forest fire risk zonation using remote sensing and GIS in Huynial watershed, TehriGarhwal district, UA. International Journal of Basic and Applied Research, 2: 6-12.
- Dimopoulou, M. and Giannikos, I. 2004. Towards an integrated framework for forest fire control. European Journal of Operational Research, 152(2): 476-486.
- Dong, X., Li-min, D., Guo-fan, S., Lei., T. and Hui, W. 2005. Forest fire risk zone mapping from satellite images and GIS for Baihe Forestry Bureau. Journal of Forestry Research, 16(3): 169-174.
- Erten, E., Kurgun, V. and Musaoglu, N. 2004. Forest fire risk zone mapping from satellite imagery and GIS: A case study. International Journal of Applied Earth Observation and Geoinformation, 4: 1-10.
- Ghodsipour, S.H. 2010. Analytical Hierarchy Process (AHP). Amirkabir University Press, Tehran, 222p (In Persian).
- Jaiswal, R.K., Mukherjee, S., Raju, K.D. and Saxena, R. 2002. Forest fire risk zone mapping from satellite imagery and GIS. International Journal of Applied Earth Observation and Geoinformation, 4(1): 1-10.
- Lee, S. 2004. Application of frequency ratio and logistic regression models to landslide susceptibility mapping using GIS. Journal of Environmental Management, 34: 223-232.
- Lee, S. and Dan, N.T. 2005. Probabilistic landslide susceptibility mapping in the Lai Chau province of Vietnam: focus on the relationship between tectonic fractures and landslides. Journal of Environmental Geology, 48: 778-787.
- Lee, S. and Pradhan, B. 2006. Probabilistic Landslide risk mapping at Penang Island, Malaysia. Journal of Earth System Science, 115: 661-672.
- Lee, S. and Talib, J.A. 2005. Probabilistic landslide susceptibility and factor effect analysis. Journal of Environmental Geology, 47: 982-990.
- Lymberopoulos, N., Papadopoulos, C., Stefanakis, E., Pantalos, N. and Lockwood, F. 1996. A GIS -based forest fire management information system. EARSel Journal–Advances in Remote Sensing, 4(1): 68-75.
- Mehregan, M.R. 2009. Operation Research. Publication of Ketabe Daneshgahi, Tehran, 256p (In Persian).
- Mahdavi, A., FallahShamsi, S.R. and Nazari, R. 2012. Forests and rangelands wildfire risk zoning using GIS and AHP techniques. Caspian Journal of Environmental Sciences, 10: 43-52.
- Mansouri, N., Nazari, R., Nasiri, P. and Gharagozlu, A.R. 2011. Planning forest fire crisis management using GIS & RS. Journal of Applies RS and GIS Techniques in Natural Resource Science, 2(3): 63-73.
- Mohammadi, F., Shabanian, N., Pourhashemi, M. and Fatehi, P. 2010. Risk zone mapping of forest fire using GIS and AHP in a part of Paveh Forests. Iranian Journal of Forest and Poplar Research, 18(4): 569-586.
- Patah, N.A., Mansor, S. and Mispan, M.R. 2000. An application of remote sensing and GIS for forest fire risk mapping. Bulletin of Malaysian Center for Remote Sensing: 54-67.
- Pradhan, B. and Lee, S. 2010. Delineation of land slide hazard areas on Penang Island, Malaysia, by using frequency ration, logistic regression, and artificial neural network model. Environmental Earth Science, 60(5): 1037-1054.
- Sanjary, S. 2007. Application Guide to ArcGIS 9.2. Abed Press, Tehran, 334p (In Persian).
- Sowmya, S.V. and Somashekar, R.K. 2010. Application of remote sensing and geographic information system in mapping forest fire risk zone at Bhadrawilflife sanctuary, India. Journal of Environmental Biology, 31(6): 969-974.
- Vadrevu, K.P. and Eaturu, A. 2009. Fire risk evaluation using multicriteria analysis-a case study. Environmental Monitoring Assessment, 166(4): 223-239.
- Viegas, D. 2004. Slope and wind effect on fire propagation. International Journal of Wild Land Fire, 13: 143-156.
Iranian Journal of Forest and Poplar Research
Volume 22, Issue 4 - Serial Number 4
January 2015
Pages 559-573

Files

Share

How to cite

Statistics