Decompositional Analysis Of UnobservedTrigger Factors Of Slope Failures Based OnStructural Equation Modeling

This paper presents a decompositional analysis of unobserved trigger factors of the slope failures based on Structural Equation Modeling (SEM). Quantitative prediction models are generally based on the relationship between past slope failures and causal factors (e.g., geology, soil, slope, aspect, etc.), and do not deal with the “trigger factors” (e.g., rainfalls, earthquakes, weathering, etc.), due to the difficulties of obtaining pixel-based observations on the triggering factors. As a measure of triggering, we have selected an inverse analysis algorithm on the trigger factors, and produced “Trigger Factor Influence maps” or TFI maps. Through that algorithm, we have indicated how a “single trigger factor” in the path model, which is generally termed a “path diagram” in the SEM approach used and discussed in this contribution, could be estimated inversely. In this contribution, we try to decompose the trigger factors into a “1 st trigger