Big data managing in a landslide early warning system: experience from a ground-based interferometric radar application

Emanuele Intrieri,Giuseppe Di Massa,Pasquale Versace,Sandra Costanzo,Riccardo Fanti,Giovanna Capparelli,Francesco Fidolini,Nicola Casagli,Federica Bardi,Antonio Raffo,Giovanni Gigli

doi:10.5194/nhess-17-1713-2017

Emanuele Intrieri, Giuseppe Di Massa + Show 9 more

Open Access

https://doi.org/10.5194/nhess-17-1713-2017

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Abstract

Abstract. 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.

Highlights

Urbanization, especially in mountain areas, can be considered a major cause for high landslide risk because of the increased exposure of elements at risk
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
The main objective was to improve the social preparedness for the growing landslide risk, according to the suggestions of several authors (Gene Corley et al, 1998; Baldridge and Marshall, 2011; Urlainis et al, 2014, 2015)

Summary

Introduction

Urbanization, especially in mountain areas, can be considered a major cause for high landslide risk because of the increased exposure of elements at risk. The main objective was to improve the social preparedness for the growing landslide risk, according to the suggestions of several authors (Gene Corley et al, 1998; Baldridge and Marshall, 2011; Urlainis et al, 2014, 2015). This led to the development of several approaches and frameworks for increasing the resiliency of society exposed to the risk (Kröger, 2008; Cagno et al, 2011, and references therein). The implementation of integrated landslides early warning systems

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