Rapid landslide susceptibility screening is important for linear engineering projects because long corridors, numerous slope units, limited data, and tight schedules often restrict the use of data-intensive models. This study develops an engineering-oriented reduced-factor screening framework based on the Information Value (IV) model and applies the framework to the Beijing-Zhangjiakou Railway corridor. A conventional 10-factor IV model was first established as the reference model. Reduced-factor models were then screened under the same study area, the same landslide inventory, the same modelling workflow, and the same factor classification scheme. The 10-factor model reached an accuracy of 94.87%. Two reduced five-factor models reached the same accuracy: Slope + Aspect + Elevation + Lithology and Engineering Rock + NDVI, and Slope + Aspect + Elevation + Lithology and Engineering Rock + Distance to Rivers. The comparison shows that the full-factor model can be simplified without loss of validation accuracy when a stable terrain–geological framework is retained and a suitable external factor is added. Because the available inventory contains only 45 landslides and does not distinguish failure mechanisms consistently, the proposed model should be regarded as a preliminary probabilistic screening tool rather than a mechanism-specific prediction model. The proposed framework provides a practical approach for corridor-scale hazard screening under incomplete data conditions.
Song et al. (2026) studied this question.