## 1 Introduction  
Landslide hazards are among the priority issues in risk assessment systems. Many landslides triggered by earthquakes have caused countless loss of life and property. Thus, landslides have caused great concern among geoscientists. At present, many scholars have researched seismic landslides from a statistical perspective [1, 2]. Multiple historical seismic landslide datasets have focused on revealing the factors and mechanisms that trigger seismic landslides. Common seismic landslide models include information models [3], random forest models [4], and artificial neural network models [5], which are statistical analysis models that are data-driven and use large amounts of historical data to obtain results when assessing regional seismic landslide hazards. Therefore, the results are objective and credible in the spatial and temporal dimensions. However, the models are restricted by inconsistent data types or limited data coverage because different earthquakes have occurred across different regions. Some scholars have researched seismic landslides from the perspective of engineering mechanics [6; 7]. Mechanical models have been mostly utilized to simulate and predict regional seismic landslide hazards by evaluating the stability of slopes with seismic structural data or relatively complete records from a single earthquake. Such models require detailed variable spatial parameters, which are effective and require less work for a single landslide. Commonly, the landslide occurrence mechanism, slope instability mechanism, and slip results are considered for grading the landslide hazard quantitatively [8]. The Newmark displacement model, a type of mechanical model, is commonly used for assessing seismic landslide hazards quantitatively on the basis of limit equilibrium theory. After the model was first proposed in 1965 [8], [PERSON] and [PERSON] [9] established an analytical model for the critical acceleration ratio on the basis of a full collection of seismic network-monitoring records over many years. [PERSON] and [PERSON] [10] incorporated GIS into the Newmark displacement model, combined with the ground motion parameters to establish a simplified Newmark model for calculating the permanent displacement of landslides. [PERSON] et al. [11] combined computer technology with the Newmark model and proposed a procedure that considers topographic effects and runout behavior for analyzing seismic landslide hazards. [PERSON] et al. [12] discussed the accuracy of the Newmark evaluation model by comparing landslides caused by the 1994 Northridge earthquake in California with landslides on the basis of landslide displacement prediction. In comparison to statistical models, the Newmark displacement model can quantitatively assess the hazard of landslides despite in the lack of actual landslide samples. Currently, it is widely used in seismic hazard assessments worldwide. Many scholars have used the Newmark displacement model to analyze landslide hazards, and have proposed improving the model by modifying the coefficients according to the characteristics of the research area [13; 14]. The application scope of the Newmark model has been extended. However, some deficiencies are reflected in the limitations of the model. [PERSON] et al. [14] established a regression equation between the probability of failure and displacement based on the landslides inventory triggered by the Northridge earthquake. But the study area selected only the epicenter area of the Northridge earthquake where landslides are densely distributed, which does not include the whole affected area, thus likely causing discrepancy with the assessment of the whole affected area. In addition, the commonly available regional geological map data are suitable for rapid emergency assessment but insufficient for the model because of the poor data accuracy or the landslide inventory not being fully utilized [15; 16]. Therefore, it is necessary to establish a parameter system to improve data accuracy for Newmark displacement model applications.