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Quantitative hazard and risk assessment for slow-moving landslides from Persistent Scatterer Interferometry

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Abstract

Preparation of reliable landslide hazard and risk maps is crucial for hazard mitigation and risk management. In recent years, various approaches have been developed for quantitative assessment of landslide hazard and risk. However, possibly due to the lack of new data, very few of these hazard and risk maps were updated after their first generation. In this study, aiming at an ongoing assessment, a novel approach for updating landslide hazard and risk maps based on Persistent Scatterer Interferometry (PSI) is introduced. The study was performed in the Arno River basin (central Italy) where most mass movements are slow-moving landslides which are properly within the detection precision of PSI point targets. In the Arno River basin, the preliminary hazard and risk assessment was performed by Catani et al. (Landslides 2:329–342, 2005) using datasets prior to 2002. In this study, the previous hazard and risk maps were updated using PSI point targets processed from 4 years (2003–2006) of RADARSAT images. Landslide hazard and risk maps for five temporal predictions of 2, 5, 10, 20 and 30 years were updated with the exposure of losses estimated in Euro (€). In particular, the result shows that in 30 years a potential loss of approximate €3.22 billion is expected due to these slow-moving landslides detected by PSI point targets.

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Acknowledgement

This work was supported by National Natural Science Foundation of China (No. 41201424), 973 National Basic Research Program (No. 2013CB733203 and No. 2013CB733204), 863 National High-Tech R&D Program (No. 2012AA121302) and Mountain Risks FP6 project of European Commission (MRTN-CT-2006-035798). The authors are grateful to the staff of Tele-Rilevamento Europa, a spin-off company of Politecnico di Milano owning the patent of PSInSAR™ technique, for the data processing and software development. The authors also thank the Arno River Basin Authority for data sharing.

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  1. College of Surveying and Geo-Informatics, Tongji University, Siping Road 1239, Shanghai, China

    Ping Lu

  2. Center for Spatial Information Science and Sustainable Development Applications, Tongji University, Siping Road 1239, Shanghai, China

    Ping Lu

  3. Department of Earth Sciences, University of Firenze, Via La Pira 4, Florence, Italy

    Filippo Catani, Veronica Tofani & Nicola Casagli

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  1. Ping Lu
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Lu, P., Catani, F., Tofani, V. et al. Quantitative hazard and risk assessment for slow-moving landslides from Persistent Scatterer Interferometry. Landslides 11, 685–696 (2014). https://doi.org/10.1007/s10346-013-0432-2

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