ABSTRACT
Predicting global landslide occurrences is very difficult and expensive in terms of time and money. Drawing upon recent advances of satellite remote sensing technology, an experimental landslide prediction model is developed to identify the timing for landslides induced by heavy rainfall, the primary trigger. Landslide warning systems can save lives and reduce damages if properly implemented in populated areas of landslide-prone nations. Comprehensive modeling of the physical processes involved in landslides helps pinpoint causes of landmass movement in relation to rainfall. In the future, increasing availability of improved, yet low-cost remote sensing products that can support GIS-based landslide models will likely benefit disaster prevention for landslide-prone regions. Prior to achieving that, the challenge facing the research community is to continue to develop techniques to better understand landslide processes that translate into potential warning applications. Such efforts must be practical with respect to local expertise and facilities available.
