Landslide Susceptibility Assessment Based on Clustering Meth

发布时间：2021-01-03 19:58

　　The aim of this study is to assess and compare two clustering algorithms,namely,the Wave-cluster and Density Based Spatial Clustering of Application with Noise（DBSCAN）algorithms,for landslide susceptibility assessment in Baota District,China.Based on historical reports,interpretation of aerial photographs and field survey reports 293 were identified in the study area.Seven factors associated with landslide occurrence were prepared and used as inputs into the models for landslide susceptibility m... 

【文章来源】：江西理工大学江西省

【文章页数】：60 页

【学位级别】：硕士

【文章目录】：
ACKNOWLEDGEMENTS
ABSTRACT
LIST OF ACRONYMS
CHAPTER1.INTRODUCTION
    1.1 Research background,purpose and significance
    1.2 Literature review
    1.3 Framework
CHAPTER2.CLUSTERING METHODS OVERVIEW
    2.1 Cluster analysis
        2.1.1 Cluster analysis concepts
        2.1.2 Clustering theory
        2.1.3 Types of data and distance measure
    2.2 Wave-cluster Algorithm
        2.2.1 Basic theory
        2.2.2 Motivation for using wavelet transforms
        2.2.3 Multiresolution analysis
        2.2.4 Procedure
    2.3 DBSCAN algorithm
        2.3.1 Basic concepts
        2.3.2 Definition of terms used in DBSCAN algorithm
        2.3.3 Density Definitions （Ester et al., 1996）
        2.3.4 DBSCAN Procedure
        2.3.5 Advantages
        2.3.6 Disadvantages
    2.4 K-Means algorithm
        2.4.1 K-means basic concepts
        2.4.2 Procedure and advantages
    2.5 Landslide Density
CHAPTER3.STUDY AREA AND MATERIALS
    3.1 Study area description
    3.2.Landslide inventories
    3.3 Landslide causative factors
CHAPTER4.LANDSLIDE SUSCEPTIBILITY ASSESSMENT
    4.1 Data preparation
    4.2 Cluster analysis using WAVE-CLUSTER and DBSCAN algorithms in landslide susceptibility assessment
    4.3 Landslide susceptibility Mapping
CHAPTER5.RESULTS AND DISCUSSION
    5.1 Model evaluation
        5.1.1 Statistical Measures
        5.1.2 ROC
    5.2 Models validation and comparison
CHAPTER6.CONCLUSIONS AND FUTURE ENHANCEMENT
REFERENCES


【参考文献】：
期刊论文
[1]Groundwater level prediction of landslide based on classification and regression tree[J]. Yannan Zhao,Yuan Li,Lifen Zhang,Qiuliang Wang.  Geodesy and Geodynamics. 2016(05)
[2]Landslide hazards mapping using uncertain Na?ve Bayesian classification method[J]. 毛伊敏,张茂省,王根龙,孙萍萍.  Journal of Central South University. 2015(09)
[3]Landslide Hazard Mapping Using GIS and Weight of Evidence Model in Qingshui River Watershed of 2008 Wenchuan Earthquake Struck Region[J]. 许冲,徐锡伟,戴福初,肖建章,谭锡斌,袁仁茂.  Journal of Earth Science. 2012(01)



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