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Change Detection and Classification of Seismic Damage with LiDAR and RADAR Surveys in Supporting Emergency Planning. The Case of Amatrice

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Computational Science and Its Applications – ICCSA 2017 (ICCSA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10407))

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Abstract

The spread of new satellite and LiDAR data is recently leading to the development of effective methodologies to support the monitoring and management of disaster risks, assessing the level of damages in the very early post-event phase. The increasing availability of SAR images and the diffusion of LiDAR data due to technologies such as solutions such as drones offers the opportunity to experiment new techniques for monitoring the territory. The paper will examine the case study of Amatrice (Central Italy), the Municipality most affected by the seismic swarm started in August 2016, and discuss the results obtained with the technique of interferometric differentiation and detection of change.

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Acknowledgements

Authors are grateful to the Civil Protection of Friuli Venezia Giulia region, for providing LiDAR dataset analyzed in this paper.

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Correspondence to Beniamino Murgante .

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Saganeiti, L., Amato, F., Potleca, M., Nolè, G., Vona, M., Murgante, B. (2017). Change Detection and Classification of Seismic Damage with LiDAR and RADAR Surveys in Supporting Emergency Planning. The Case of Amatrice. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10407. Springer, Cham. https://doi.org/10.1007/978-3-319-62401-3_53

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  • DOI: https://doi.org/10.1007/978-3-319-62401-3_53

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-62401-3

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