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  DOI Prefix   10.20431


 

International Journal of Constructive Research in Civil Engineering
Volume 3, Issue 4, 2017, Page No: 67-75
doi:dx.doi.org/10.20431/2454-8693.0304006

Fire Risk Potential Checking in Forests using Fire Risk Model

Sayed Ali Hasheminasab1,Mojtaba Pirnazar2,Sayed Hafez Hasheminasab3,ArashZand Karimi4,Saeid Eslamian5,Kaveh Ostad-Ali-Askari6,Vijay P.Singh7,Nicolas R.Dalezios8,Mohsen Ghane9,Ali Mirkhalafi10

1.Department of Natural Resources, Yasooj University, Yasooj, Iran.
2.Department of Remote Sensing, Tabriz University, Tabriz, Iran.
3.Water Engineering Department, Isfahan University of Technology, Isfahan, Iran.
4.Department of Civil Engineering, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
5.Department of Biological and Agricultural Engineering &Zachry Department of Civil Engineering, Texas A and M University, 321 Scoates Hall, 2117 TAMU, College Station, Texas 77843-2117, U.S.A.
6.Laboratory of Hydrology, Department of Civil Engineering, University of Thessaly, Volos, Greece & Department of Natural Resources Development and Agricultural Engineering, Agricultural University of Athens, Athens, Greece.
7.Department of Civil Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.

Citation :Sayed Ali Hasheminasab,et.al, Fire Risk Potential Checking in Forests using Fire Risk Model International Journal of Constructive Research in Civil Engineering 2017,3(4) : 67-75

Abstract

Forests are one of the most valuable wealth on the earth planet and are living place for animals and plants, so protecting of them is an important and necessary order. One of the main reasons of forest annihilation is not controlled fires that destroy wide areas of forest and cause desertification. Remote sensing and GIS can be so much beneficial for studying Fire risk. In this research we investigated fire risk in protected forests in Central Alborz that has occurred every year and caused to plenty of damages. In this research Fire Risk method was used which included gradient environment factors, gradient direction and vegetation cover. Eventually area's fire risk maps were prepared which had weak relation with previous fire data and this point demonstrates low efficiency of presented model.


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