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The signal of the seafloor is identified and removed and the noise is filtered setting a threshold for the intensity values. Then the pings are stacked with the values of the water column backscatter intensity for each beam over time. Observing the point with higher intensity it is possible to reconstruct the path of the ML type within the specified beam. To estimate the sinking velocity a portion of the stacked pings is selected on the basis of the minimum and maximum number of pings and depths extracted with FM Midwater when the ASCII files where created. The selected window corresponds to the time interval when the ML is freely falling in the water column. The first input asks for a link to a .zip file containing the ASCII .txt data of the water column backscatter intensity values extracted with FM Midwater and a .inp file containing the values of the window used to calculate the sinking velocity. The second input (“working_dir”) is need only to specify the work directory when workin in a local machine. https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/author https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/contentSize 23184 https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/contentUrl https://api.rohub.org/api/ros/c4be06dc-6af4-4bc1-8843-035e943a54ad/crate/download/ https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/contributor http://everest.psnc.pl/users/antonio.petrizzo https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/creator http://everest.psnc.pl/users/antonio.petrizzo https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/dateCreated 2019-12-05 10:40:09.490000+00:00 https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/dateModified 2025-03-05 01:19:07.077298+00:00 https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/datePublished 2019-12-05 10:40:09.490000+00:00 https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/description It calculates the sink velocity of a net floating in water starting from water column data. https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/encodingFormat application/ld+json https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/funder EASME/EMFF/2017/1.2.1.12/S2/05/SI2.789314 https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/hasPart https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/folders/59557620-b13f-4b2d-876d-d035af6ae9a2 https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/hasPart https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/folders/d66c8c1b-f8d7-4990-82df-41075c519d64 https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/hasPart https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/folders/d75cec1c-2268-4433-81bf-74f698031055 https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/hasPart https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/folders/e543c7fa-ded9-4db3-a7c7-8d3b9f26c2b3 https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/hasPart https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/resources/82efe8bd-0252-4d6c-803a-8dfc8a305b49 https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/identifier https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/keywords MarGnet, net, sink velocity, water column, backscatter https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://schema.org/name SinkVel https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://www.acsys.it/everest#vrc Sea Monitoring https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/ro#ResearchObject https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/roevo#LiveRO https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#WorkflowResearchObject https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/Dataset https://w3id.org/ro-id/c4be06dc-6af4-4bc1-8843-035e943a54ad/ https://www.w3.org/ns/iana/link-relations/relation#cite-as Aleksandra Kruss (ISMAR-CNR Venice), Antonio Petrizzo (ISMAR-CNR Venice), Fantina Madricardo (ISMAR-CNR Venice), Lukasz Janowski (University of Gdansk), and Antonio Petrizzo. "SinkVel." ROHub. 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