A big challenge in terms or landslide risk mitigation is represented by
increasing the resiliency of society exposed to the risk. Among the
possible strategies with which to reach this goal, there is the implementation of
early warning systems. This paper describes a procedure to improve early warning
activities in areas affected by high landslide risk, such as those
classified as critical infrastructures for their central role in society.
This research is part of the project LEWIS (Landslides Early Warning
Integrated System): An Integrated System for Landslide Monitoring, Early
Warning and Risk Mitigation along Lifelines.
LEWIS is composed of a susceptibility assessment methodology providing
information for single points and areal monitoring systems, a data
transmission network and a data collecting and processing center (DCPC),
where readings from all monitoring systems and mathematical models converge
and which sets the basis for warning and intervention activities.
The aim of this paper is to show how logistic issues linked to advanced
monitoring techniques, such as big data transfer and storing, can be dealt
with compatibly with an early warning system. Therefore, we focus on the
interaction between an areal monitoring tool (a ground-based interferometric
radar) and the DCPC. By converting complex data into ASCII strings and
through appropriate data cropping and average, and by implementing an
algorithm for line-of-sight correction, we managed to reduce the data daily
output without compromising the capability for performing
