Landslides triggered by rainfall can possibly be foreseen 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 landslides due to the lack of sufficient ground-based observing network 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 a preliminary real-time prediction system to
identify where rainfall-triggered landslides will occur is proposed by combining two necessary
components: surface landslide susceptibility and a real-time space-based rainfall analysis system
(http://trmm.gsfc.nasa.gov
). First, a global landslide susceptibility map is derived from a combination
of semi-static global surface characteristics (digital elevation topography, slope, soil types, soil texture,
land cover classification, etc.) using a GIS weighted linear combination approach. Second, an adjusted
empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess
landslide hazards at areas with high susceptibility. A major outcome of this work 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 preliminary system can be updated
continuously using the new satellite remote sensing products. This proposed system, if pursued through
wide interdisciplinary 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.
Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, nosystem exists at either a national or a global scale to monitor or detect rainfall conditions that maytrigger landslides due to the lack of sufficient ground-based observing network in many parts of theworld. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity forsuch a study. In this paper, a framework for developing a preliminary real-time prediction system toidentify where rainfall-triggered landslides will occur is proposed by combining two necessarycomponents: surface landslide susceptibility and a real-time space-based rainfall analysis system(http://trmm.gsfc.nasa.gov). First, a global landslide susceptibility map is derived from a combinationof semi-static global surface characteristics (digital elevation topography, slope, soil types, soil texture,land cover classification, etc.) using a GIS weighted linear combination approach. Second, an adjustedempirical relationship between rainfall intensity-duration and landslide occurrence is used to assesslandslide hazards at areas with high susceptibility. A major outcome of this work is the availability forthe first time of a global assessment of landslide hazards, which is only possible because of theutilization of global satellite remote sensing products. This preliminary system can be updatedcontinuously using the new satellite remote sensing products. This proposed system, if pursued throughwide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslidehazard analyses into a global decision-making support system for landslide disaster preparedness andmitigation activities across the world.
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