Open AccessModeling and mapping forest fire risk in the region of Aures (Algeria)
Author(s) -
Souad Rahmani,
Hassen Benmassoud
Publication year - 2020
Publication title -
geoadria
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.118
H-Index - 3
eISSN - 1848-9710
pISSN - 1331-2294
DOI - 10.15291/geoadria.2846
Subject(s) - vulnerability (computing) , geographic information system , geography , vegetation (pathology) , class (philosophy) , situated , cartography , remote sensing , environmental resource management , environmental science , computer science , artificial intelligence , medicine , computer security , pathology
The objective of this study is to modeling and mapping the Forest fire risk in the region of Aures situated in Northeast of Algeria, through the application of multi-criteria analysis methods to integrate geographic information systems (GIS) and remote sensing. The methodology is based on a weighted linear combination of three parameters that influence the initiation and propagation of a forest fire. These are vegetation, topography and anthropogenic index. The result is a vulnerability map classified into four classes according to pixel values. very high risk class forms 18,28% of the study area, high risk class forms 42,42%, moderate risk class forms 5,24% and 34,05% of the area is low risk.