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Showing 2 results for Ahp Method

Nader Oveisi, Solmaz Khazaei Moghani , Naser Bay,
Volume 6, Issue 4 (1-2015)
Abstract

Introduction: Landslide is one of the natural hazards around the country that cause casualties and financial losses each year. This disaster destroyed roads, meadows, mountains, erosion, and sedimentation in the watershed basins.
Method: In this study, the risk of landslides in Golestan province is examined via weighted (using AHP) bivariate statistical model. First, all the landslides (number & area) were listed by field study based on local data, and then the distribution map was prepared for each city.
Findings: According to the results, relative risk map was prepared with six classes. The highest and lowest number of landslides occurred in Maraveh Tappeh and Aq Qala respectively. The most area of landslides was in Aliabad. In addition, Ali Abad and Kalaleh Kordkuy county and also Gonbad, Ramian, Bandar Torkaman, Gomishan had the most and the least hazard rate.
Conclusion: The analysis of effective factors for landslide showed that landslide factors have different importance.
Ali Dastranj, Hamzeh Noor, Ali Bagherian Kalat,
Volume 14, Issue 1 (2-2022)
Abstract

INTRODUCTION: Landslides are one of the recurrent natural problems that are widespread throughout the world, especially in mountainous areas, and cause a significant injury to and loss of human life and damage to properties and infrastructures. This study aimed to assess landslide susceptibility using the analytic hierarchy process (AHP) in Binalood mountains, Razavi Khorasan Province, Iran.
METHODS: Since the Binalood Mountains range has a high potential for landslides occurrence, the present study went through to map landslide susceptibility. To accomplish this, the AHP method was used, and then, receiver operating characteristic/Area Under the Curves (AUCs) were prepared to evaluate the performance of the susceptibility map. Multiple data, such as lithology, distance to faults, land use, distance to roads, altitude, slope, aspect, stream power index, topographic wetness index, rainfall, distance from rivers, slope length index, and topographic location index, were considered for delineating the landslide susceptibility maps. These thematic layers were assigned suitable weights on the Saaty's scale according to their relative importance in landslide occurrence in the study area. The assigned weights of the thematic layers and their features were subsequently normalized using the AHP technique. Finally, all thematic layers were integrated by a weighted linear combination method in a geographic information system tool to generate landslide susceptibility maps.

FINDINGS: The landslide susceptibility maps are split into five classes, namely very low, low, moderate, high, and very high. The results showed that the geological factor was the most important factor affecting the occurrence of landslides in the study area. Generally, 47.8% of the total area was considered high and very high-risk areas. The prediction accuracy of this map showed the values of AUC equal to 81.7% that showed the AHP model had very good accuracy.
CONCLUSION: AHP is acceptable for landslide susceptibility mapping in the study area. A landslide susceptibility map is a useful tool to help with land management in landslide-prone areas. The results revealed that the predicted susceptibility levels were found to be in good agreement with the past landslide occurrences. Possibly, this map can be used by the concerned authorities in disaster management planning to prepare rescue routes, service centers and shelters.


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