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Combined Photogrammetric and Laser Scanning Survey to Support Fluvial Sediment Transport Analyses

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Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12252))

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Abstract

This paper presents the contribution of digital surveying techniques for the estimation of fluvial sediment transport. The aim is to create predictive models able to minimize or reduce the hydrogeological hazard, especially before or during critical meteorological events. The case study is the Caldone stream, a watercourse located in the municipality of Lecco (Italy). Structure-from-Motion photogrammetry and terrestrial laser scanning techniques were used to collect metric data about the morphology of the riverbed. Data acquisition was carried out to create a digital model of visible and submerged parts of the riverbed. Then, a second area with a sedimentation pool was selected to monitor the variation of the depth induced by progressive accumulation of sediments. As the pool is constantly covered by water, a low-cost bathymetric drone was used coupling the measured depth values with total station measurements to track the drone. Finally, the paper describes the implementation of an on-line data delivery platform able to facilitate retrieval of heterogeneous geospatial data, which are used in the developed numerical model for sediment transport. This service aims at providing simplified access to specific map layers without requiring knowledge about data formats and reference systems.

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Acknowledgments

This work has been financed by Fondazione Cariplo in the framework of the “SMART-SED project: Sustainable MAnagement of sediment transpoRT in responSE to climate change conditions,” grant no. 2017–0722. The authors want to thank Laura Longoni and Davide Brambilla (Politecnico di Milano, Dept. of Environmental and Civil Eng.) for the coordination during the project and the development of the floating device used in the sedimentation pool. We want to thank you also to Valentina Conca and Claudio Sironi for their help during the on-site survey carried out for their thesis.

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Authors and Affiliations

  1. ABC Department, Politecnico di Milano, via Ponzio 31, 20133, Milan, Italy

    Luigi Barazzetti, Riccardo Valente, Mattia Previtali & Marco Scaioni

  2. Polo territoriale di Lecco, Politecnico di Milano, via G. Previati 1/c, 23900, Lecco, Italy

    Fabio Roncoroni

Authors
  1. Luigi Barazzetti
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  2. Riccardo Valente
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  3. Fabio Roncoroni
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  4. Mattia Previtali
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  5. Marco Scaioni
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Corresponding author

Correspondence to Luigi Barazzetti .

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Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Chair- Center of ICT/ICE, Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Clayton School of Information Technology, Monash University, Clayton, VIC, Australia

    David Taniar

  7. Department of Information Science, Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

  11. Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA

    Yeliz Karaca

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Barazzetti, L., Valente, R., Roncoroni, F., Previtali, M., Scaioni, M. (2020). Combined Photogrammetric and Laser Scanning Survey to Support Fluvial Sediment Transport Analyses. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12252. Springer, Cham. https://doi.org/10.1007/978-3-030-58811-3_45

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  • DOI: https://doi.org/10.1007/978-3-030-58811-3_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58810-6

  • Online ISBN: 978-3-030-58811-3

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