| As a kind of secondary disasters caused by strong earthquakes, the earthquake-induced landslide has drawn much attention in the world because of severe hazards it causes. In a mountainous region, sometimes a great loss of lives and properties caused by landslide even exceeds the losses caused by the earthquake itself. These large landslides usually cannot be prevented by current mitigating measures, whereas the only possible preventive measures are early warning and evacuation of vulnerable communities. In order to reduce the damage, researches on the potential earthquake-induced landslide zoning are conducting in many countries at present. The purpose of the zoning map is to provide a tool for regional planning. Based on it, the government can avoid the dangerous areas and select suitable sites for constructions, thereby protect peoples' lives and properties.In southwest China, due to its complex geological and geographical conditions, many strong earthquakes have occurred, inducing lots of landslide, therefore, earthquake-induced landslide remains one of the most serious seismic hazards there. So, the study of this issue is very important in theory as well as practice especially when our government is implementing the grand strategy to develop western China.Supported by hundreds of bibliographies, this thesis systemically details the earthquake-induced landslide's distribution characteristics, formation conditions and related influencing factors. Based on previous research results, this work summarizes relationships between landslides and influencing factors, such as geological background, rock mass structure, topography as well as hydrogeology condition. Also, this thesis gives a brief glance to the methods used in the slope stability study and puts forward some improvements to the old methods. In this work, Geographic Information System(GIS) technology has been used as a power tool in the research. The question concerned is the spatial features that meet the GIS capacity very well. Spatial database has the ability of controlling all the data from diverse sources, and the factors influencing earthquake-induced landslide which are taken into account have different combinations as known. So, in this thesis, all the factors have been studied together on a uniform platform supported by GIS instead of studying single factors independently.The studies show that earthquake-induced landslide is not distributed at random, rather it has its regularity. It means the corresponding relationship between the earthquake- induced landslide and the geological factors, though it is a non-linear relationship. This work uses neural network named Radial Basis Probabilistic Neural Network(RBPNN) to study this non-linear relationship through the training of landslide samples. In terms of geo-technological structure analogy, to determine the potential landslide places is essentially a pattern recognition question, because the areas where earthquake-induced landslides occur have similar geology conditions. Through repeated sample training, neural network could obtain the model of relationship, and then the model can be used to simulate the potential area that would be influenced by earthquake-induced landslide. The non-linear relationship obtained through neural network training would be more objective than others because the whole process is fulfilled automaticly. In this work, rivers, faults, rock, slope angle and seismic intensity are taken as the neutral network input indexes into account of the existing knowledge of the landslide.It is known that there are many factors influencing earthquake-induced landslide, and different factors have different actions to the same thing. Due to both a great variation in landslide characteristics and our insufficient understanding on mechanisms of landslide, traditional methods in deciding factors' weights mainly depend on the experts' experiences, so the results would be subjective to some degree. Analytic Hierarchy Process(AHP) is a good technical approach for converting subjective assessment into a set of weight. It has proven to be very useful in assisting selection from a finite set of alternatives as well as in ranking things. Through comparing factors two by two, pairwise comparison matrix is built, after solving the matrix, weights of relative importance for different factors are obtained. Despite of the complexity of the factor ranking, there is another difficult problem needing to be solved. It is difficult to give a clear boundary for different earthquake-induced landslide hazard grades when we need to tell where the area is more danger than another. Fuzzy Mathematics is good helpful to solve this question. Building a single factor influence matrix according to the grades needed (in this work, the risk is divided into 3 grades: high hazard area, middle hazard area and no hazard area), synthesis it with the weight matrix obtained by AHP, and then a degree of membership matrix is obtained. At last, the hazard grade is decided by the maximal membership degree. The application of AHP and Fussy mathematics could be a useful attempt in the hazard zoning work.In this thesis, three examples are taken and used as target areas to apply the method presented above. They are the Luhuo Earthquake(1973, M=7.9), Lijiang Earthquake(1996, M=7.0) and Zhaotong Earthquake(1974, M=7.1). All of the three earthquakes occurred in southwest China and triggered lots of landslides. Specific steps of analysis are as follows:(1) After the study of every strong earthquake triggered landslides' distribution, selecting training samples and constructing neural network for every example earthquake, then use the neutral network model to simulate the potential area influenced by earthquake-induced landslide. The results show the good capacity of neutral network in landslide area recognition.(2) Based on the neutral network identifying in different areas, this work takes all the training samples together to obtain a uniform model. The results also show the good capacity of neutral network in landslide area recognition.(3) Based on the study of relationships between rivers, faults, rock, slope angle, seismic intensity and distribution of earthquake-induced landslide, this work decides weights of relative importance for the 5 factors using AHP technique and builds single factor influence matrix(A) at the same time. The weights matrix(W) of the 5 factors is: W= (0.04910.1379 0.3393 01850 0.2855) . Further more, fussy synthesis of 2 matrix is made: B -WOA, where B is a matrix of the final evaluation. This work classes the hazard areas into 3 grades: high hazard area, moderate hazard area and no hazard area. From the zoning results, it's clear that almost the entire area influenced by earthquake-induced landslide has been enclosed in the high hazard range. In summary, this thesis selects 5 factors out of all influencing earthquake-induced landslide to study its distribution. The results indicate that the 5 factors are scientific and of utility in the neutral network input index and AHP fuzzy mathematics. The neutral network model drawn from the Luhuo earthquake, Lijiang earthquake and Zhaotong earthquake can be used as a tool to identify the dangerous areas which have similar geological conditions and support the land planning. It's also worth attention that in different geological settings, the same factor may have different actions and different weights.
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