Landslide susceptibility modeling and mapping of Antipolo Rizal through heuristic, deterministic and statistical methodologies - Victor, Jaime Angelo S.; Zarco, Mark Albert H. (Quezon City College of Engineering, University of the Philippines Diliman, 2015)
The determination of probability of landslide occurrence is the first step in landslide risk assessment. Landslide susceptibility assessment of Anti polo City, Rizal was performed using three approaches: heuristic, statistical, and deterministic . This study aims to evaluate, compare and cross validate the three methods and generate a landslide susceptibility map of Antipolo, Rizal. This study also analyzes the potential of using geoinformatic methods with classical geotechnical theories in providing reliable susceptibility assessment results, considering both morphometric and non-morphometric factors. The Landslide Susceptibility Index (LSI) modeling uses the heuristic approach, giving equal weights to the identified causative factors. The higher the LSI, the more the area is susceptible to landslide occurrence. The LSI model classified by quantiles was evaluated to have a success rate of 74.67% and prediction rate of 75.39%. The logistic regression modeling implements a statistical approach based on maximum likelihood of landslide occurrence based on combinations of identified causative factors. Among the five models developed using logistic regression, designated Model 1 was chosen as the best predictor model, with corresponding success rate of 90.7%, 91.66% over-all accuracy, AUROC of 0.908, and lowest root mean square error of 0.2478. The third approach uses the deterministic SINMAP modeling that combines the infinite slope stability model and a steady state hydrological model. This method concludes that 41.56% and 22.26% of Antipolo lie on areas of low and moderate susceptibility to landslide occurrence . The remaining area is identified to have high ( 13.35%) and very high (22.44%) likelihood of landslide occurrence. To compare the maps generated from the three models, overlay analys is of the landslide inventory was performed. It was found out that the statistacal model performed best in classifying the landslides with a success rate of 88.8%, followed by SINMAP model with success rate of 80.4%. The LSI method has the lowest success rate of 74.9%. The agreement of the three models was also evaluated. The agreement with respect to the total area covered and landslide events were computed to be 54. 1 % and 58.36%, respectively.
Includes appendices.
Thesis (M.S. in Civil Engineering)--University of the Philippines Diliman
Keywords: Landslides -- Philippines -- Risk assessment; Landslide hazard analysis -- Antipolo City (Philippines).