Forest fire hazard zone mapping in Ilam county forests

Document Type : Scientific article

Authors

1 Master of Forestry Student, Faculty of Natural Resource and Environment, Malayer University, Malayer, I. R. Iran.

2 Assistant Professor, Department of Rangeland and Watershed Management, Faculty of Natural Resource and Environment, Malayer University, Malayer, I. R. Iran.

3 Associate Professor, Department of Forestry, Faculty of Natural Resource, Ilam University, Ilam, I. R. Iran.

Abstract

Several factors play an important role in the occurrence of fire in forests. So accurate prediction of the time and place of the fire is difficult, but using the GIS, it is possible to identify points of high fire risk. The purpose of this study was to investigate the possibility of preparing a fire hazard zonation map for Ilam district. Socioeconomic, climatic, topographic and vegetation factors were considered as suitable criteria for assessing the status of fire risk of these forests and were evalutaed Using satellite imagery data, geographic information system and neural network system. According to the results, the variable of distance from cities with a weight of 100% is the most influential variable in creating fire and height variable with a weight of 1.5% as the least important variable in the occurrence of forest fire in study area. Based on the results of the assessment of the accuracy of the fire hazard zonation map using the error matrix, it was found that the produced map with a general accuracy of 73.73% is highly true. Also, based on Kappa agreement coefficient (0.77) between the map and actual fire data, it can be concluded that the map prepared with the actual data was highly adapted.

Keywords

References

- Aleemahmoodi Sarab, S., J. Feghhi., B. Jabbarian Amiri., A. Danehkar & P. Attarod, 2014. Applying the regression models to assess the influences of climate factors on forest fires (case study: Izeh), Journal of Natural Environment (IranianJournal of Natural Rssources), 66(2): 191-201. (In Persian)
- Alonso-Betanzos, A., O. Fontenla-Romero., B. Guijarro-Berdin˜as., E. Herna´ndezPereira., E. Canda., J. Jimenez., J. Luis Legido., S. Mun˜iz., C. Paz-Andrade & M.I. Paz-Andrade, 2002. A neural network approach for forest fire risk estimation.In: F. van Harmelen, (Ed.), Proceedings of the 15th European Conference onArtificial Intelligence. ECAI’2002, Lyon, France, 643–647.
- Amiri, T., A. Banj Shafiei., M. Erfanian., O. Hosseinzadeh & H. Beygi Heidarlou, 2017. Determining of effective criteria in locating firefighting station in forest, Journal of Forest Research and Development, 2(4): 379-393. (In Persian)
- Beygi Heidarlu, H., A. Banj Shafiei & M. Erfanian, 2015. Forest fire risk mapping using analytical hierarchy process technique and frequency ratio method (Case study: Sardasht Forests, NW Iran), Iranian Journal of Forest and Poplar Research, 22(4): 559-573. (In Persian)
- Beygi Heidarlu, H., A. Banj Shafiei & M. Erfanian, 2015. Evaluating the Fuzzy Weighted Linear Combination Method in Forest Fire Risk Mapping (Case study: Sardasht Forests, West Azerbaijan Province, IRAN), Journal of Wood & Forest Science and Technology, 22(3): 29-51. (In Persian)
- Chamandeh, J., S. Alvaninejad & P. Gholami, 2017. A survey of composition and diversity of herbaceous species after a fire in Persian Oak forests of Southern Zagros, Journal of Wood & Forest Science and Technology, 24(3): 1-15. (In Persian)
- Chandra, S. 2005. Application of remote sensing and GIS technology in forest fire risk modeling and management of forest fires: A case study in the Garhwal Himalayan Region, Geo-information for Disaster Management, 1239-1254.
- Chuvieco, E & E.S. Kasischke, 2007. Remote sensing information for fire management and fire effects assessment, Journal of geophysical research, 112: 1-8.
- Chuvieco, E. & R.G. Congalton, 1989. Application of remote sensing and geographic information systems to forest fire hazard mapping, Remote Sensing of Environment, 29:147–159.
- Costa Freitas, M.B., A. Xavier & R. Fragoso, 2017. Integration of Fire Risk in a Sustainable Forest Management Model, Forests, 8: 1-20.
- Darvishi, L., M. Ghodskhah & V. Gholami, 2013. A regional model for forest fire hazard zonation in forests of Dorud city (Case Study: Babahar region), Iranian Journal of Forest and Range Protection Research, 11(1): 10-20. (In Persian)
- Dong, X.U., D. Li-min., SH. Guo-fan., T. Lei, & W. Hui, 2005. Forest fire risk zone mapping from satellite images and GIS for Baihe Forestry Bureau Jilin, China, Journal of Forestry Research, 16 (3):169-174.
- Esmaili Sharif, M., H. Jalilvand., M. Amoozad., A. A. Jafari & S. M. Moslemi SeyedMahle, 2018. The effect of ecological factors on fire in Hyrcanian forests (Case study: forest areas of Neka, azandaran, Iran), Journal of Forest Research and Development, 4(1):113-129. (In Persian)
- Feizizadeh, B & M. Hajimirrahimi, 2007. Application of remote sensing data in land use mapping, Geomatics Congress 87, Tehran, Mapping Organization of Iran, https://www.civilica.com/Paper-GEO87-GEO87_060.html. (In Persian)
- Giglio, L. 2010. MODIS Collection 5 Active Fire Product User's Guide Version 2.4, Science Systems and Applications, Inc. University of Maryland, Department of Geography, 61 p.
- Hemmatboland, I., M. Akbarinia & A. Banej Shafiei, 2010. The effect of fire on some soil chemical properties of oak forests in Marivan region, Iranian Journal of Forest and Poplar Research, 18(2): 205-218. (In Persian)
- Heydari, M & M. Faramarzi, 2015. Short term effects of fire with different intensities on the composition and diversity of soil seed bank in the Zagros forest ecosystem, Sirvan, Applied Ecology, 3(9):57-68. (In Persian)
- Hernandez-Leal, P.A., M. Arbelo & A. Gonzalez- Calvo, 2006. Fire risk assessment using satellite data, Advances in Space Research, 37(4):741-746.
- Iliadis, L.S. 2005. A decision support system applying an integrated fuzzy model for long-term forest fire risk estimation, Environmental Modelingand Software, 20(5):613–621.
- Jaiswal, K.R., S. Mukherjee., D.R. Kumaran & R. Saxena, 2002. Forest fire risk zone mapping from satellite imagery and GIS, International Journal of Applied Earth Observation and Geoinformation, 4(1):1-10.
- Khashei M., M. Bijari & GH. A. Raissi, 2009, Improvement of Auto-Regressive Integrated Moving Average Models Using Fuzzy Logic and Artificial Neural Networks (ANNs), Neurocomputing, 72: 956–967. (In Persian)
- Kocher, S & V. Butsic, 2017. Governance of Land Use Planning to Reduce Fire Risk to Homes Mediterranean France and California, Land, 6(24):1-18.
- Mahdavi, A. 2012. Forests and rangelands? Wildfire risk zoning using GIS and AHP techniques, Caspian Journal of Environmental Sciences, 10(1):43-52. (In Persian)
- Martı´nez, J., C. Vega-Garcia & E. Chuvieco, 2009. Human caused wildfire risk rating for prevention planning in Spain, Journal of Environmental Management, 90(2):1241–1252.
- Martell, D.L. S. Otukol & B.J. Stocks, 1987. A logistic model for predicting daily people-caused forest fire occurrence in Ontario, Canadian Journal of Forest Research, 17(5):394-401.
- Mirdeylami, T & SH. Shataei, 2011. An analysis of spatial prediction and spatial modeling of fire hazard in natural resources, the first international conference on natural resources in Gorgan, Iran. (In Persian)
- Mobargai, N., GH. Sharzhei., M. Makhdoum., A.R. Yavari & H.R. Jafari, 2009. The spatial valuation pattern of Co2 absorption function in Caspian forests of Iran, Journal of Enviromental Studies, 35(50): 57-68. (In Persian)
- Mohammadi, F., N. Shabanian., M. Pourhashemi & P. Fatehi, 2009. 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. (In Persian)
- Nirabadi, H & M. Hajimirrahimi, 2007. Application of hierarchical and fuzzy methods in landfill location, Geomatics Congress 87, Tehran, Mapping Organization of Iran, civilica.com/Paper-GEO87-GEO87_036.html. (In Persian)
- Polat, S., F. Ghasemi Aghbash & A. Mahdavi. 2018. Mapping of Distribution of Forest Fire Risk in Forests by Using Neural Networks and Geographic Information System (Case study: Ilam forests). MS.C Thesis, Malayer University, 125p.
- Puri, K., G. Areendran., K. Raj., S. Mazumdar & P. K. Joshi. 2011. Forest fire risk assessment in parts of Northeast India using geospatial tools. Journal of Forestry Research, 22(4): 641-647.
- Sadeghifar, M., A. Beheshti Ale Agha & M. Pourreza, 2016. Variability of Soil Nutrients and Aggregate Stability in Different Times after Fire in Zagros Forests (Case Study: Paveh Forests), Ecology of Iranian Forests, 4(8): 19-27. (In Persian)
- Salamati, H., H. Mostafa Lou., A. Mastoori & F. Honardoust, 2011. Assessment and mapping forest fire risk using GIS in Golestan province - forests. Abstracts of 1st International Conference on Wildfire in Natural Resources Lands, Iran, pp. 10. (In Persian)
- Sharma, D., V. Hoa., T.V. Cuong., H.T. Tuyen & N. Sharma, 2009. Forest Fire Risk Zonation for Jammu District forest division using Remote Sensing and GIS. 7th FIG Regional Conference. Spatial Data Serving People: Land Governance and the Environment – Building the Capacity. Hanoi, Vietnam, 19-22.
- Vadrevu, K.P., A. Eaturu & K.V.S. Badarinath, 2010. Fire risk evaluation using multi-criteria analysis– a case study, Environmental Monitoring and Assessment, 166 (1-4): 223–239.
Forest Research and Development
Volume 6, Issue 1
June 2020
Pages 135-152

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