Use of geospatial data and fuzzy algebraic operators to landslide-hazard mapping

Geospatial data base creation for landslidehazard mapping is often an almost inhibitive activity. This has been the reason that for quite some time landslide-hazard analysis was modeled on the basis of spatially related factors. This paper presents the use of fuzzy logic to landslide-hazard analysis in the Penang Island, Malaysia, using remote sensing data and a geographic information system (GIS). To achieve the goal, a data-derived model (frequency ratio) and a knowledge-derived model (fuzzy operator) were combined for landslide-hazard analysis. Landslide locations within the study areas were identified by interpreting aerial photographs, satellite images and field surveys. The nine factors that influence landslide occurrence were extracted from the database and the frequency ratio coefficient for each factor was computed. Using the factors and the identified landslide, the fuzzy membership values were calculated. Then fuzzy algebraic operators were applied to the fuzzy membership values for landslidehazard mapping. Finally, the produced map was verified by comparing with existing landslide locations for calculating prediction accuracy. Among the fuzzy operators, in the case in which the gamma operator (lambda=0.8) showed the best accuracy (80%) while the case in which the fuzzy or operator was applied showed the worst accuracy (56%).