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Computer-Aided Geomorphic Seabed Classification and Habitat Mapping at Punta Licosa MPA, Southern Italy

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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 12250))

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Abstract

Accurate seafloor maps serve as a critical component for understanding marine ecosystems and are essential for marine spatial planning, management of submerged cultural heritage and hazard risk assessments. In September 2001 the Marine Protected Area (MPA) of Punta Licosa has been mapped using a multibeam echosounder (MBES) and a side scan sonar (SSS) system in support of the Geosed project. Such seabed investigations has allowed for high-resolution bathymetric measurements and acoustic seafloor characterization through backscatter imagery.

Based on visual interpretation of the data, the present study utilized a computer-aided seabed classification approach to map marine landform features and seabed composition of the study area. The results were then translated into a complete coverage geomorphologic map of the area to define benthic habitats. Offshore shelf plain make up more than half of the region (52.2%), with the terraces making up another 10.2% of the total area. Slopes make up a cumulative 30.1% of the study area. Scarp features comprise 4.3% while ridge features reach only 3.2% of the total study area. Benefits of the computer-aided seabed classification approach used in this study consisted in a fairly accurate geomorphic classification, while the effectiveness of a semi-automated approach for identifying substrate composition from backscatter data mostly relied on the level of acoustic artefacts present within the survey area.

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Acknowledgments

I am grateful to the Master of R/Vs Urania and Thetis Captains Emanuele Gentile and Aimone Patanè and all the crewmembers for their significant contribution to the geophysical survey operations. Thanks also to the two anonymous reviewers who provided valuable feedback which greatly improved the manuscript. This work was supported by the project PON-IDEHA, Innovation for Data Elaboration in Heritage Areas, financed by the Italian Ministry of the University and Scientific and Technologic Research.

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Authors and Affiliations

  1. Institute of Heritage Science, CNR, Via G. San Felice, 8, Naples, Italy

    Crescenzo Violante

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  1. Crescenzo Violante
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Correspondence to Crescenzo Violante .

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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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Violante, C. (2020). Computer-Aided Geomorphic Seabed Classification and Habitat Mapping at Punta Licosa MPA, Southern Italy. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12250. Springer, Cham. https://doi.org/10.1007/978-3-030-58802-1_49

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  • DOI: https://doi.org/10.1007/978-3-030-58802-1_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58801-4

  • Online ISBN: 978-3-030-58802-1

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