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Understanding the spatial and temporal occurrence of landslides using satellite and airborne technologies: Papua New Guinea
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Conclusions
This researchhas demonstrated that freely-availableandpre-existingdata canbeused toanalyseanddevelopmodels
to inform landslide early warning/forecasting systems, in a data sparse region, such as PNG. It has been shown that
probabilistic rainfall thresholds can be developed using satellite-derived rainfall estimates and that satellite and
airborne remote sensing methods can be used to construct high resolution models of landslide susceptibility. As
with any modelling framework, there are a number of caveats and assumptions associated with the triggering-event
and landslide susceptibility models that need to be carefully considered. There is also a requirement for further
testing and calibration of the models prior to any real-world application. However, the techniques and data outlined
provide a cost-effective, robust and reproducible modelling framework, which could be employed by a range of
users to inform of periods of heightened landslide susceptibility. The relationships identified and the potential of this
modelling framework could be used to help mitigate landslide hazard in the region and, ultimately, reduce losses
associated with these events.
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