Developing Tools for Earthquake-induced Landslide Hazard Maps of the Island of Hawai`i

The purpose of this study is to develop earthquake-induced landslide hazard maps for the Island of Hawai'i using various tools such as Geographical Information Systems (GIS), Artificial Intelligence (AI), and Logistic Regression (LR). The methodology for the current research consists of developing empirical models based on factors considered to be most influential on landslide susceptibility, and analytical models based on conventional slope stability analysis. Earthquake- induced landslide hazard maps were then developed using these models for the Island of Hawai'i.;Empirical models involve systematically studying the landslide contributing factors for the entire island without using any slope stability model. This can be applied to the entire island with generally available island-wide spatial data. Empirical models involve the use of various techniques such as weight analysis, logistic regression and AI based tool such as ANFIS (Adaptive Neuro Fuzzy Inference System). The maps developed using empirical models can help in selecting regions where further study on slope stability is necessary. For these selected regions, slope stability analysis was carried out with new empirical models developed using explanatory variables from an analytical slope-stability model.;In latter models, the general approach to the landslide zoning method is based on conventional slope stability analyses to determine the Factor of Safety (FS) and critical ground (yield) acceleration (ay) of the individual slopes based on profiles and specific geotechnical and seismic information. Due to inadequate peak shear strength data for the studied regions, along with other considerations, a residual friction angle prediction model using ANFIS was developed based upon available data pairs of residual friction angle and available soil parameters for various locations around the world, including some in Hawai'i. The (or These) derived residual friction angle data were then used in slope stability analyses.;For the Island of Hawai'i, a new PGA prediction model was developed using ANFIS. This model can reconstruct the PGA for any historical earthquake or future hypothetical earthquake. Hence, PGA values for various historical earthquakes and one hypothetical earthquake were derived using ANFIS. Based upon the calculated difference between these PGA values and ay, earthquake-induced landslide hazard zoning maps with ten zones viz., high (1) to low (0), have been developed. These maps provide hazard status values for various geographically distributed earthquake scenarios.;The landslide hazard maps developed here can be utilized to prioritize further investigation and to highlight where further recommendations on mitigation methodologies may be appropriate. After establishing hazard zones on a landslide hazard map, a detailed site-specific study can be done and necessary slide preventive measures can be taken. The earthquake-induced landslide hazard zoning maps may provide valuable information on the slope stability of large areas, and may be of interest for land use, infrastructure planning, engineering, and hazard mitigation design. The methodologies formulated here could be easily transported to other regions where evaluations of preliminary earthquake-induced landslide potential are desired, especially where data are sparse and/or where regional evaluations have yet to be undertaken. (Abstract shortened by UMI.).