Marine Geophysical Research

, Volume 40, Issue 3, pp 333–355 | Cite as

Seabed mapping in the Pelagie Islands marine protected area (Sicily Channel, southern Mediterranean) using Remote Sensing Object Based Image Analysis (RSOBIA)

  • Sara InnangiEmail author
  • Renato Tonielli
  • Claudia Romagnoli
  • Francesca Budillon
  • Gabriella Di Martino
  • Michele Innangi
  • Roberta Laterza
  • Tim Le Bas
  • Claudio Lo Iacono
Original Research Paper


In this paper we present the seabed maps of the shallow-water areas of Lampedusa and Linosa, belonging to the Pelagie Islands Marine Protected Area. Two surveys were carried out (“Lampedusa 2015” and “Linosa 2016”) to collect bathymetric and acoustic backscatter data through the use of a Reson SeaBat 7125 high-resolution multibeam system. Ground-truth data, in the form of grab samples and diver video-observations, were also collected during both surveys. Sediment samples were analyzed for grain size, while video images were analyzed and described revealing the acoustic seabed and other bio-physical characteristics. A map of seabed classification, including sediment types and seagrass distribution, was produced using the tool Remote Sensing Object Based Image Analysis (RSOBIA) by integrating information derived from backscatter data and bathy-morphological features, validated by ground-truth data. This allows to create a first seabed maps (i.e. benthoscape classification), of Lampedusa and Linosa, at scale 1:20 000 and 1:32 000, respectively, that will be checked and implemented through further surveys. The results point out a very rich and largely variable marine ecosystem on the seabed surrounding the two islands, with the occurrence of priority habitats, and will be of support for a more comprehensive maritime spatial planning of the Marine Protected Area.


Multibeam bathymetry Backscatter Benthoscapes Seabed classification Ground-truth data Posidonia oceanica Coralligenous habitat 



We thank Simone D’Ippolito, the captain of the M/B ‘Risal’, for the help and continuous support during all the operations of data acquisition. Thanks to the crew of the R/V ‘Minerva Uno’, for all the support during board and research operations. The authors wish to thank Sergio Monteleone and Patricia Scaflani for their comments to the first draft of the manuscript.


This study benefited from contribution of the project “Implementation of research activity and monitoring around Pelagie Islands Marine Protected Area”, within the project “CAmBiA – Contabilità Ambientale e Bilancio Ambientale” funded by the Ministry of the Environment and Protection of Land and Sea (MATTM – Ministero dell’Ambiente e della Tutela del Territorio e del Mare), directive n° 5135 of march 2015. This study also benefited from the contribution of the RITMARE Flagship Project, funded by Ministry of Education, University and Research (MIUR – Ministero dell’Istruzione dell’Università e della Ricerca) [NRP 2011–2013].

Supplementary material

11001_2018_9371_MOESM1_ESM.pdf (3.5 mb)
Supplementary material 1 (PDF 3599 KB) A) High resolution DTM of Linosa island and shallow water offshore (2.5 × 2.5 m pixel resolution) with 5 m contouring. The location of bathymetric transects T’1 and T’2 is indicated, as well as ground-truth points (Rov and grab samples position). B) High resolution snippet mosaic of Linosa island and shallow water offshore (2.5 × 2.5 m pixel resolution) with 5 m contouring.
11001_2018_9371_MOESM2_ESM.pdf (3.2 mb)
Supplementary material 2 (PDF 3314 KB) A) High resolution DTM of Lampedusa island and shallow water offshore (2.5 × 2.5 m pixel resolution) with 5 m contouring. The location of bathymetric transects T1 and T2 is indicated, as well as video points position. B) High resolution snippet mosaic of Lampedusa island and shallow water offshore (2.5 × 2.5 m pixel resolution) with 5 m contouring.
11001_2018_9371_MOESM3_ESM.pdf (2.3 mb)
Supplementary material 3 (PDF 2382 KB) 1 Raster images used to analyze the Lampedusa seabed with RSOBIA. a) Snippet mosaic (backscatter), where the brightness values are given (low value corresponding to high backscatter and low absorption); b) DTM image (in meters); c) the surface roughness (in dimensionless value) derived trough RSOBIA; d): the slope image (in degree) derived trough RSOBIA. 2 RSOBIA segmentation results: a) shows the BD segmentation; b) shows the BDRS segmentation. The maps show the majority, the most common class of all pixels in polygon. This is the main class for interpretation. 3 Pairwise comparison of the two segmentations for a sector of Lampedusa. The BDRS segmentation shows a better recognition of the acoustic facies boundaries compared to BD segmentation. For this reason, it was decided to adopt the BDRS segmentation for the interpretation.


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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • Sara Innangi
    • 1
    Email author
  • Renato Tonielli
    • 1
  • Claudia Romagnoli
    • 2
  • Francesca Budillon
    • 1
  • Gabriella Di Martino
    • 1
  • Michele Innangi
    • 3
  • Roberta Laterza
    • 5
  • Tim Le Bas
    • 4
  • Claudio Lo Iacono
    • 4
  1. 1.Istituto di Scienze Marine, CNRNapoliItaly
  2. 2.Dipartimento di Scienze Biologiche, Geologiche ed AmbientaliUniversità di BolognaBolognaItaly
  3. 3.Dipartimento di Scienze e Tecnologie Ambientali, Biologiche e FarmaceuticheUniversità degli Studi della Campania “Luigi Vanvitelli”CasertaItaly
  4. 4.National Oceanography CentreUniversity of SouthamptonSouthamptonUK
  5. 5.Senior GeophysicistLiverpoolUK

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