A hybrid model to overcome landslide inventory incompleteness issue for landslide susceptibility prediction.

Landslide inventory incompleteness (LII) may significantly affect the model performance in landslide susceptibility mapping (LSM). However, traditional methods, including heuristic, statistical and deterministic models, cannot address LII issue. In this work, we introduce a novel hybrid LEO-MAHP model, blending landslide frequency, empirical adjustments, optimization functions, and multi-participated analytic hierarchy process to address it by taking Badong County as the study area. This hybrid model mitigates the drawbacks of data-heavy statistical approaches and subjective heuristic models by incorporating LII into weight determination. The findings show that the LEO-MAHP model demonstrates superior performance (AUROC = 0.809 and 0.805) over conventional statistical (AUROC = 0.714 and 0.770) and heuristic models (AUROC = 0.738 and 0.741) across different LII levels. We further discuss alternative LII solutions, proposing an updated landslide management strategy that accounts for climate change and human activities. Our findings underscore the necessity of evaluating LII before applying statistical or machine learning methods in LSM. List of Abbreviations: AHP: Analytic hierarchy process; AUROC: Area under receiver operating characteristic curve; CR: Consistency ratio; CI: Consistency index; CF: Conditional factor; DEM: Digital elevation model; FN: False negative; FP: False positive; FPR: False positive rate; InSAR: Interferometric Synthetic Aperture Radar; IV: Information value; LD: Landslide density; LII: Landslide inventory incompleteness; LS: Landside susceptibility; LSI: Landslide susceptibility index; LSM: Landslide susceptibility mapping; MAHP: Multi-participated analytic hierarchy process; MC: Model construction; MCDA: Multi-criteria decision analysis; MV: Model verification; MPP: Model prediction performance; ORS: Optical remote sensing; P&C: Prevention and control; PGA: peak ground acceleration; ROC: Receiver operating characteristic; RI: Random index; TN: True negative; TP: True positive; TPR: True positive rate. [ABSTRACT FROM AUTHOR]