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Regional Hazard Assessment of Disaster Environment for Debris Flows: Taking Jundu Mountain, Beijing as an Example
详细信息   
摘要
///In this paper,three analysis methods,such as,factors weighting-superposition one,information amount model one and FCM-rough set one,are firstly presented and analyzed.FCM-rough set method integrates the advantages of fuzzy C-means clustering method(FCM) and rough set theory,which is a data-driven method.On the basis of spatial distributions of 339 gully numbers of the debris flows from field surveying in Jundu Mountains of Beijing,hazard assessment maps of the debris flows are compiled based on the three methods,and then the assessment results are compared.The conclusions can be drawn as follows: 1) the methods of factors weighting-superposition one and information amount model one can draw 5 levels of hazard classification results of debris flows,by contrast,FCM-rough set method can only draw 3 levels of classification results; 2) based on the results of the three assessment methods,on the whole,gully numbers of debris flows in the hazard zones increase,when hazard assessment levels change from low to high; 3) taking the actual gully numbers of debris flows located in different hazard zones as judging standard,information amount model method can obtain better results,which possesses more than 90% of gully numbers of debris flows in high and very high hazard zones;FCM-rough set method can reach 63.72% of the gully distribution of debris flows in dangerous zones; and 4) taking ratio of gully numbers within unit area and gully distribution of debris flows as judging standard,and information amount model method is relatively good to the general gully distribution of debris flows,which possesses high precision evaluation.The results obtained by factors weighting-superposition method have not obvious difference in high and very high hazard zones,and a good gradient is not formed.FCM-rough set method covers most of gully distribution of debris flows in dangerous zones,but its calculation results are not good,and the method could be promoted in other similar regional disaster environment for future study.

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