Landslide Risk Assessments through Multicriteria Analysis

被引:5
作者
Chaabane, Fatma Zohra [1 ,2 ]
Lamine, Salim [3 ,4 ]
Guettouche, Mohamed Said [1 ]
El Islam Bachari, Nour [4 ]
Hallal, Nassim [5 ]
机构
[1] Univ Sci & Technol Houari Boumedien USTHB, Lab Geomorphol & Geohazards G&G, Directorate Gen Sci Res & Technol Dev DGRSDT, BP 32 El Alia, Algiers 16111, Algeria
[2] Univ Sci & Technol Houari Boumedien USTHB, Lab Geophys LGEOPHY, Directorate Gen Sci Res & Technol Dev DGRSDT, BP 32 El Alia, Algiers 16111, Algeria
[3] Higher Sch Saharan Agr Adrar, Adrar 01000, Algeria
[4] Univ Sci & Technol Houari Boumedien USTHB, Lab Biol Oceanog & Marine Environm LOBEM, BP 32 El Alia, Algiers 16111, Algeria
[5] Res Ctr Astron & Astrophys CRAAG, Route Observ,BP 63, Algiers 16032, Algeria
关键词
Landsat data; image processing; ArcGIS; analytical hierarchy process; weighted sum; multicriteria analysis; GIS; SUSCEPTIBILITY;
D O I
10.3390/ijgi13090303
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Natural risks comprise a whole range of disasters and dangers, requiring comprehensive management through advanced assessment, forecasting, and warning systems. Our specific focus is on landslides in difficult terrains. The evaluation of landslide risks employs sophisticated multicriteria models, such as the weighted sum GIS approach, which integrates qualitative parameters. Despite the challenges posed by the rugged terrain in Northern Algeria, it is paradoxically home to a dense population attracted by valuable hydro-agricultural resources. The goal of our research is to study landslide risks in these areas, particularly in the Mila region, with the aim of constructing a mathematical model that integrates both hazard and vulnerability considerations. This complex process identifies threats and their determining factors, including geomorphology and socio-economic conditions. We developed two algorithms, the analytic hierarchy process (AHP) and the fuzzy analytic hierarchy process (FAHP), to prioritize criteria and sub-criteria by assigning weights to them, aiming to find the optimal solution. By integrating multi-source data, including satellite images and in situ measurements, into a GIS and applying the two algorithms, we successfully generated landslide susceptibility maps. The FAHP method demonstrated a higher capacity to manage uncertainty and specialist assessment errors. Finally, a comparison between the developed risk map and the observed risk inventory map revealed a strong correlation between the thematic datasets.
引用
收藏
页数:27
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