Saeid Hamzeh; Afshin Amiri
Abstract
Extended Abstract Introduction As a type of mass movement involving slow or rapid movement of soil, rock material or both on the lower hillsides, landslide is under the effect of gravity.Landslide is recognized as one of the most common geological disasters causing worldwide damages and casualties.Landslide ...
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Extended Abstract Introduction As a type of mass movement involving slow or rapid movement of soil, rock material or both on the lower hillsides, landslide is under the effect of gravity.Landslide is recognized as one of the most common geological disasters causing worldwide damages and casualties.Landslide susceptibility maps provide important and valuable information,including time scale of possible future landslides, which are usedfor predicting landslide hazards. Since predicting the time of landslide occurrence is beyond the capability of science and knowledge, identifying areas susceptible to landslide and ranking them can extensively restrict the damages caused by landslide. Therefore, it is essential to zone landslide risk and identify factors affecting it. Analytic Network Process(ANP) is aGIS-based Multi-Criteria Decision Analysis(GIS MCDA) method successfully applied to many decision-making systems. The present study seeks to evaluate landslide risk and achieve a zoning map for the sub-basin under study using ANP and Weighted Overlaymethods. Materials and Methods Based on the literature and using different experts’ viewpoint, criteria affecting landslide risk were identified and five major criteria including topography, land use and land cover, geology, hydrometry and infrastructure were selected. The selected criteria include the following sub-criteria: slope, slope direction, curvature, elevation, lithology, soil type, land use, vegetation density, distance from roads, distance from habitat, river and drainage density and precipitation. The effective factor layers were standardized and a specific scale was defined for their units.Then, each layer was assigned a weight based on its role and importanceusing Analytic Network Process.Proposed to modify Analytic Hierarchical Process(AHP), this method (ANP) relies on the analyses of the human brain for complex and fuzzy problems.Network Analysis Process generally includes the following steps: determining indicators, criteria and options;classifying identified criteria into clusters and elements; determining the relationship between clusters, elements and options; performing pairwise comparisons between clusters, elements and options, and finally calculating the final weight of elements and options. UsingWeightedOverlaymethod, these elements were then integrated with their related coefficients and the final landslide risk map was obtained. Results and discussion Each criteria and sub-criteria were weighted using Analytic Network Processmethod.Topographic and land cover criteria had the most and hydrographic criteria had the least impact on the landslide occurrence. According to the final map, most landslides have occurred in eastern and southern slopes at an altitude of 500 to 2,200 meters. Moreover, 17/31% of the study area was located in the very high-risk class and 33% in the high risk class (about half of the area has high potential of landslide). Previous landslide data were used to assess the landslide zoning map results. Results indicate that most landslides have occurred in the high risk class (about 35% of landslides) and only about 4% of landslides have occurred in the very low risk class. Conclusion Landslide is one of the natural hazards causing serious harms and problems for human life. Identifying the factors affecting landslide and zoning its hazard is especially important for the identification of risky and susceptible areas.So, landslides were selected as one of the main topics of the study with the aim of controlling and managing its hazards.The ANP network analysis method was used to model and predict landslide risk in this research.Each criteria and sub-criteria were weighted and overlapped to producethe map of relative landsliderisk.The lowest risk was observed in the northern parts of the region, and the highest landslide risk was observed in the northern hillsides with higher humidity.WeightedOverlaymethod and network analysis model were effective in predicting landslide susceptibility and producing landslide zoning map.
Reza Aghataher; Mohammad Fallah Zezoli; Mehrdad Zarafshar; Mohsen Jafari
Abstract
The present research was conducted with the aim of locating the susceptible military centers and determining the favorable areas for its construction in a part of dense forests in Golestan province-Ali Abad Katoulcity, using the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS). ...
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The present research was conducted with the aim of locating the susceptible military centers and determining the favorable areas for its construction in a part of dense forests in Golestan province-Ali Abad Katoulcity, using the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS). For this purpose, using defense experts’ opinions, university professors, military experts and resources review, information layers, slope percentage, slope direction, elevation classes, distance from the canal network, distance from the road, distance from villages, lithology, density of vegetation and distance from urban areas as factors affecting the location of susceptible military centers in forest areas were identified and the aforementioned maps were prepared and digitized in the GIS environment.In the next step, standard AHP forms were prepared and assigned to different experts in order to weight and prioritize effective factors. Weighted forms were collected and each of them was analyzed separately in Expert Choice software and AHP module in Arc GIS 9.3 software. Finally, the weight of each of the criteria and sub-criteria related to the target was determined. The results of the evaluation showed that the three factors of distance from the city (0.321), distance from the road (0.217) and lithology (0.176) have had the most impacts on the location of the susceptible defense centers of the study area, while the density of the vegetation (0.023) and direction of slope (0.017) have had the least effects. Eventually, the final potential map of the susceptible defense centers was prepared using the AHP model in the GIS software environment, and was divided into four subcategories of low potential (9.07%), medium (41.8%), high (30.01%) and very high (19.13%).
