Refined susceptibility assessment of landslides in township—Taking Xiongjia Township,Wanzhou District as an example
The study of landslide susceptibility at the township is of great significance for subsequent local hazard risks prevention and control.Exploring the susceptibility assessment method suitable for the accura-cy requirements of township-level assessment and refined survey data has become the focus of research.Xiongjia Township in Wanzhou District is taken as the study area.On the basis of refined geological hazard investigation,the landslide hazards are subdivided into deep-seated colluvial landslides and shallow colluvial landslides,and the slope units are divided respectively.Based on the landslide mechanisms,different suscep-tibility assessment indexes are proposed.Aiming at the challenge of insufficient landslide samples in the township scale area and the difficulty of using statistical and machine learning assessment methods,a multi classification logistic regression model is introduced to assess the susceptibility of study area with insuffi-cient samples.Combining landslide units,non-landslide units and unstable slope units with certain deforma-tion but no overall slip,the traditional binary variables of 0 and 1 are broken through,and the sample set including"intermediate state"variables is constructed,so as to realize the effective expansion of landslide samples and quantitative assessment of different degrees of susceptibility.The results show that the ex-tremely high and high susceptibility areas of shallow colluvial landslides are mainly located in the north of the study area and the central and southern areas with intense human activities,and 70.59％of the defor-mation slopes are located in high-extremely high susceptibility areas.The extremely high and high suscepti-bility areas of deep-seated colluvial landslide are mainly distributed on both sides of the river with gentle slope in the west,and the accuracy AUC of the evaluation results is 0.823.This study has reference value for the investigation and assessment of landslide risk in township scale and the equivalent scales.
deep-seated colluvial landslideshallow colluvial landslidesusceptibility assessmentmulti clas-sification logistic regression model
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