Automatic detection of MLs targets from the bathymetry
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Marine litter Sacca Fisola, Venice, 2021
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description: The shape files contain the marine litter targets both manually identified and obtained as output of the ArcGis workflow applied to the input bathymetry
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sd date published: 2023-09-20 10:18:03.270442+00:00

Valentina Grande
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Bathymetry Sacca Fisola, Venice, 2021
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description: Data collected in October 2021 by CNR- ISMAR VE within the MAELSTROM project with the aim to map marine litter on the seafloor
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sd date published: 2023-09-20 10:16:11.100932+00:00

Marine Litter Targets Identification
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description: This Notebook provides a workflow of ArcGis toolboxes to identify ML targets from bathynetry.
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sd date published: 2023-09-20 08:14:51.618953+00:00

Workflow requirements
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Scientific paper - Semi-automated characterisation of seabed pockmarks in the central North Sea
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description: This paper presents a semi-automated method to recognize, spatially delineate and characterise morphometrically pockmarks at the seabed
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Automatic detection of MLs targets from the bathymetry
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date created: 2023-09-19 20:25:33.253021+00:00
date modified: 2025-10-16 13:13:44.987089+00:00
date published: 2023-09-19 20:25:33.253021+00:00
description: A dedicated workflow in ArcGIS (shared as Jupyter notebook) was developed to identify targets from the bathymetry within the MAELSTROM Project - Smart technology for MArinE Litter SusTainable RemOval and Management. In that framework, the workflow identified marine litter on the seafloor starting from a bathymetric surface collected in Sacca Fisola (Venice Lagoon) on 2021.
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publisher: www.ismar.cnr.it
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cite-as: Petrizzo, Antonio, Fantina Madricardo, Vanessa Moschino, and Valentina Grande. "Automatic detection of MLs targets from the bathymetry." ROHub. Sep 19 ,2023. https://w3id.org/ro-id/058215c9-d7d3-4e78-8f49-5655f899d5e3.

Antonio Petrizzo
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Fantina Madricardo
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Vanessa Moschino
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description: Marine Litter Identification from Bathymetry
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sd date published: 2023-09-19 20:43:16.422044+00:00

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DELIVERABLE 3.2.2 Research Object with the experiment data and the algorithm
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description: EASME/EMFF/2017/1.2.1.12/S2/05/SI2.789314 MarGnet official document with description of ROs developed within MarGnet Project
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DELIVERABLE 3.2.1 Report on the experimental results
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DELIVERABLE 3.3.1 Report on the survey and elaborated data in the Italian survey area (final version)
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Research Object - SinkTrack
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description: It reads and elaborates ASCII file produced with FM Midwater in order to calculate some statistics, mean, standard deviation of backscatter, depth, angle of net for each ping, and to produce a graph with the track of the net
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Research Object - SinkVel
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sd date published: 2023-09-20 10:02:58.537650+00:00

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