Modelling of forest fire risk spatial distribution in the region of Aures, Algeria
Souad Rahmani
; University of Batna 2, Faculty of Nature and Life Sciences, Department of Ecology and Environment, Laboratory for Improvement of Agricultural Production and the Protection of Ecosystems in Arid Zones, Batna, Algeria
Hassen Benmassoud
; University of Batna 1, Institute of Veterinary Sciences and Agronomic Sciences, Department of Agricultural Sciences, Laboratory for Improvement of Agricultural Production and the Protection of Ecosystems in Arid Zones, Batna, Algeria
APA 6th Edition Rahmani, S. i Benmassoud, H. (2019). Modelling of forest fire risk spatial distribution in the region of Aures, Algeria
. Geoadria, 24 (2), 79-91. https://doi.org/10.15291/geoadria.2846
MLA 8th Edition Rahmani, Souad i Hassen Benmassoud. "Modelling of forest fire risk spatial distribution in the region of Aures, Algeria
." Geoadria, vol. 24, br. 2, 2019, str. 79-91. https://doi.org/10.15291/geoadria.2846. Citirano 20.04.2021.
Chicago 17th Edition Rahmani, Souad i Hassen Benmassoud. "Modelling of forest fire risk spatial distribution in the region of Aures, Algeria
." Geoadria 24, br. 2 (2019): 79-91. https://doi.org/10.15291/geoadria.2846
Harvard Rahmani, S., i Benmassoud, H. (2019). 'Modelling of forest fire risk spatial distribution in the region of Aures, Algeria
', Geoadria, 24(2), str. 79-91. https://doi.org/10.15291/geoadria.2846
Vancouver Rahmani S, Benmassoud H. Modelling of forest fire risk spatial distribution in the region of Aures, Algeria
. Geoadria [Internet]. 2019 [pristupljeno 20.04.2021.];24(2):79-91. https://doi.org/10.15291/geoadria.2846
IEEE S. Rahmani i H. Benmassoud, "Modelling of forest fire risk spatial distribution in the region of Aures, Algeria
", Geoadria, vol.24, br. 2, str. 79-91, 2019. [Online]. https://doi.org/10.15291/geoadria.2846
Sažetak The objective of this study is to model and map the forest fire risk in the region of Aures situated in the northeast of Algeria, through the application of Analytical Hierarchy Process (AHP) method to integrate geographic information systems (GIS) and remote sensing. The methodology is based on a weighted linear combination of three parameters, namely, vegetation, topography and the anthropogenic factor which influences the initiation and propagation of a forest fire. The result is a risk map with four classes according to pixel values, whereas very high-risk class takes up 18.28% of the study area, high-risk class takes up 42.42%, moderate risk class takes up 5.24% and low-risk class takes up 34.05%.