A probabilistic approach to predictive spatial data fusion for geological hazard assessment

Geological hazards including landslides have caused extensive damage to property and sometimes result in loss of life. Thus, it is necessary to assess vulnerable areas for future landslides in order to mitigate the damage they cause. For this purpose, GIS-based spatial data fusion has been developed and applied to landslide hazard analysis. Among various methods, this paper investigates and discusses the effectiveness of probabilistic data fusion based on a permanence of updating ratio for landslide hazard mapping, which can be applied in presence of complex data interdependence. In this approach, several data sets related to landslide occurrences are digitally represented and combined using the incremental relative contribution function. To illustrate the scheme, a case study from Boeun, Korea was carried out.