Application of environmental variables in statistically-based landslide susceptibility mapping: A review

Environmental variables are crucial factors affecting the development and distribution of landslides, they also provide vitally important information for statistically-based landslide susceptibility mapping (SLSM). The acquisition utilization appropriate most influential environmental their combinations improving quality SLSM results. However, compared with construction models based on machine learning, high-quality have received very little attention. In order to further clarify research status application possible directions in future research, this study systematically analyzed SLSM. To end, a literature database was constructed by collecting 261 peer-reviewed articles (from 2002 2021) from Web Science CNKI platform ( www.cnki.net ) keywords “landslide susceptibility” “environmental variable.” We found that existing methods determining do not consider regional representativeness geomorphological significance variables. at present, utilized generally without realization understanding spatial heterogeneity. Accordingly, raises two major scientific issues: 1) Effective identification required 2) representation heterogeneity modeling. From perspective dominant geospatial pattern heterogeneity, targeted solutions preliminarily discussed, including method identifying qualitative quantitative perspectives model considering specific patterns. addition, applicability limitation mentioned discussed.