Grande Valentina

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Last Name
Grande
First Name
Valentina
ORCID
0000-0002-3489-268X

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Now showing 1 - 2 of 2
  • Article
    Application of hyperspectral imaging to underwater habitat mapping, Southern Adriatic Sea
    (MDPI, 2019-05-16) Foglini, Federica ; Grande, Valentina ; Marchese, Fabio ; Bracchi, Valentina A. ; Prampolini, Mariacristina ; Angeletti, Lorenzo ; Castellan, Giorgio ; Chimienti, Giovanni ; Hansen, Ingrid M. ; Gudmundsen, Magne ; Meroni, Agostino N. ; Mercorella, Alessandra ; Vertino, Agostina ; Badalamenti, Fabio ; Corselli, Cesare ; Erdal, Ivar ; Martorelli, Eleonora ; Savini, Alessandra ; Taviani, Marco
    Hyperspectral imagers enable the collection of high-resolution spectral images exploitable for the supervised classification of habitats and objects of interest (OOI). Although this is a well-established technology for the study of subaerial environments, Ecotone AS has developed an underwater hyperspectral imager (UHI) system to explore the properties of the seafloor. The aim of the project is to evaluate the potential of this instrument for mapping and monitoring benthic habitats in shallow and deep-water environments. For the first time, we tested this system at two sites in the Southern Adriatic Sea (Mediterranean Sea): the cold-water coral (CWC) habitat in the Bari Canyon and the Coralligenous habitat off Brindisi. We created a spectral library for each site, considering the different substrates and the main OOI reaching, where possible, the lower taxonomic rank. We applied the spectral angle mapper (SAM) supervised classification to map the areal extent of the Coralligenous and to recognize the major CWC habitat-formers. Despite some technical problems, the first results demonstrate the suitability of the UHI camera for habitat mapping and seabed monitoring, through the achievement of quantifiable and repeatable classifications.
  • Article
    Benthic habitat map of the southern Adriatic Sea (Mediterranean Sea) from object-based image analysis of multi-source acoustic backscatter data
    (MDPI, 2021-07-24) Prampolini, Mariacristina ; Angeletti, Lorenzo ; Castellan, Giorgio ; Grande, Valentina ; Le Bas, Tim ; Taviani, Marco ; Foglini, Federica
    A huge amount of seabed acoustic reflectivity data has been acquired from the east to the west side of the southern Adriatic Sea (Mediterranean Sea) in the last 18 years by CNR-ISMAR. These data have been used for geological, biological and habitat mapping purposes, but a single and consistent interpretation of them has never been carried out. Here, we aimed at coherently interpreting acoustic data images of the seafloor to produce a benthic habitat map of the southern Adriatic Sea showing the spatial distribution of substrates and biological communities within the basin. The methodology here applied consists of a semi-automated classification of acoustic reflectivity, bathymetry and bathymetric derivatives images through object-based image analysis (OBIA) performed by using the ArcGIS tool RSOBIA (Remote Sensing OBIA). This unsupervised image segmentation was carried out on each cruise dataset separately, then classified and validated through comparison with bottom samples, images, and prior knowledge of the study areas.