Experimental global prediction system for rainfall-triggered landslides using satellite remote sensing and geospatial datasets

Abstract—Landslides triggered by rainfall can possibly be fore-seen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger land-slides due to the lack of sufficient ground-based observing net-work in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing an experimental real-time prediction system to identify where rainfall-triggered landslides will occur is proposed by combining two necessary components: surface landslide susceptibility (LS) and a real-time space-based rain-fall analysis system. First, a global LS map is derived from a combination of semistatic global surface characteristics (dig-ital elevation topography, slope, soil types, soil texture, land cover classification, etc.) using a geographic information system weighted linear combination approach. Second, an adjusted em-pirical relationship between rainfall intensity-duration and land-slide occurrence is used to assess landslide hazards at areas with high susceptibility. A major outcome of this paper is the availability for the first time of a global assessment of landslide hazards, which is only possible because of the utilization of global satellite remote sensing products. This experimental system can be updated continuously using the new satellite remote sensing products. This proposed system, if pursued through wide inter-disciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and mitigation activities across the world. Index Terms—Landslide, landslide susceptibility (LS), natural disasters, real-time precipitation analysis, satellite remote sensing. I