Landslide Susceptibility Zonation Based on the Analytic Hierarchy Process and Information Method

2014 ◽  
Vol 580-583 ◽  
pp. 2658-2662
Author(s):  
Dan Dan Qiu ◽  
Rui Qing Niu ◽  
Yan Nan Zhao
Keyword(s):  
Analytic Hierarchy Process ◽  
Landslide Susceptibility ◽  
Impact Factors ◽  
Three Gorges Reservoir Area ◽  
Disaster Prevention ◽  
Analytic Hierarchy ◽  
Landslide Susceptibility Zonation ◽  
Slope Structure ◽  
Information Method ◽  
Hierarchy Process

Landslide susceptibility zonation is one of the research hotspots in the field of landslide research. It is important in the process of disaster prevention and land planning. Select Wan Zhou as study area; it is one portion of the Three Gorges Reservoir Area. According to existing landslide statistical data, select lithology, slope gradient, slope structure and reservoir grade as impact factors. Use analytic hierarchy process and information method to calculate weighted value of each factor respectively, and then combine them. The landslide susceptibility zonation was done by ArcGIS. This method can unite the advantages of the disaster data and expert experience. According to statistics, result accuracy rate is 90.3%.The key area of landslide disaster prevention can be obtained from the landslide susceptibility zonation map.

scholarly journals Performance Evaluation of Five GIS-Based Models for Landslide Susceptibility Prediction and Mapping: A Case Study of Kaiyang County, China

2021 ◽  
Vol 13 (11) ◽  
pp. 6441
Author(s):  
Yigen Qin ◽  
Genlan Yang ◽  
Kunpeng Lu ◽  
Qianzheng Sun ◽  
Jin Xie ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Analytic Hierarchy Process ◽  
Landslide Susceptibility ◽  
Vegetation Index ◽  
Characteristic Curve ◽  
Landslide Susceptibility Mapping ◽  
Analytic Hierarchy ◽  
Geological Conditions ◽  
Slope Structure ◽  
Hierarchy Process

This study evaluated causative factors in landslide susceptibility assessments and compared the performance of five landslide susceptibility models based on the certainty factor (CF), logistic regression (LR), analytic hierarchy process (AHP), coupled CF–analytic hierarchy process (CF-AHP), and CF–logistic regression (CF-LR). Kaiyang County, China, has complex geological conditions and frequent landslide disasters. Based on field observations, nine influencing factors, namely, altitude, slope, topographic relief, aspect, engineering geological rock group, slope structure, distance to faults, distance to rivers, and normalized difference vegetation index, were extracted using the raster data model. The precision of the five models was tested using the distribution of disaster points for each grade and receiver operating characteristic curve. The results showed that the landslide frequency ratios accounted for more than 75% within the high and very high susceptibility zones according to the model prediction, and the AUC evaluating precision was 0.853, 0.712, 0.871, 0.873, and 0.895, respectively. The accuracy sequencing of the five models was CF-LR > CF-AHP > LR > CF > AHP, indicating that the CF-AHP and CF-LR models are better than the others. This study provides a reliable method for landslide susceptibility mapping at the county-level resolution.

Multicriteria Evaluation of the Selection of Green Glazing Material by Using the Analytic Hierarchy Process (AHP)

2011 ◽  
Vol 224 ◽  
pp. 152-158 ◽  
Author(s):  
Cheng Chen Chen ◽  
Che Ming Chiang ◽  
Richard S. Horng ◽  
Shin Ku Lee
Keyword(s):  
Analytic Hierarchy Process ◽  
Negative Impact ◽  
Material Selection ◽  
Selection Criterion ◽  
Living Environment ◽  
Impact Factors ◽  
Hazardous Substance ◽  
Analytic Hierarchy ◽  
Glass Material ◽  
Hierarchy Process

The window glazing system provides comfortable living environment for residents and also exhibits the esthetics of architectural design. Its quality is dependent upon glass material selection; there are many factors determining glazing material selection, which might further affects the building safety and energy savings. An analytic hierarchy process (AHP) is used to analyze the trade-off of these impact factors. In the survey, both positive and negative impact factors on the glazing material selection are considered. The results, based on 40 expertise questionnaires, indicated that “performance”, in overall, was perceived to be most important core selection criterion for the green glazing material, but among all assessed items, “hazardous substance release” was concerned the most. The “appearance” was regarded as a minor factor in this analysis. In addition, BIPV alternative was also ranked in the first position regardless of criteria weight variations. The results provide valuable information for building material manufacturers, architects and interior designers in selecting glass material in their the glazing system.

Application of earth observation datasets and Analytic Hierarchy Process in the mapping of Landslide hazard zones of Manipur, India

2021 ◽  
Author(s):  
Digvijay Singh ◽  
Arnab Laha
Keyword(s):  
Analytic Hierarchy Process ◽  
Landslide Susceptibility ◽  
Landslide Hazard ◽  
Susceptibility Map ◽  
Hazard Map ◽  
Landslide Susceptibility Map ◽  
Analytic Hierarchy ◽  
High Hazard ◽  
Hierarchy Process ◽  
Very High

<p>Landslides problems are one of the major natural hazards in the mountainous region. Every year due to the increase in anthropogenic factors and changing climate, the problem of landslides is increasing, which leads to huge loss of property and life. Landslide is a common and regular phenomenon in most of the northeastern states of India.  However, in recent past years, Manipur has experienced several landslides including mudslides during the rainy season. Manipur is a geologically young and geodynamically active area with many streams flowing parallel to fault lines. As a first step toward hazard management, a landslide susceptibility map is the prime necessity of the region. In this study, we have prepared a landslide hazard map of the state using freely available earth observations datasets and multi-criteria decision making technique, i.e., Analytic Hierarchy Process (AHP). For this purpose, lithology, rainfall, slope, aspect, relative relief, Topographic Wetness Index, and distance from road, river and fault were used as the parameters in AHP based on the understanding of their influence towards landslide in that region. The hazard map is classified into four hazard zones: Very High, High, Moderate, and Low. About 40% of the state falls under very high and high hazard zone, and the hilly regions such as Senapati and Chandel district are more susceptible to the landslide. Among the factors, slope and rainfall have a more significant contribution towards landslide hazard. It is also observed that areas nearer to NH-39 that lies in the fault zones i.e., Mao is also susceptible to high hazard. The landslide susceptibility map gives an first-hand impression for future land use planning and hazard mitigation purpose.</p>

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