dc.creatorRevollo Sarmiento, Natalia Veronica
dc.creatorDelrieux, Claudio Augusto
dc.date.accessioned2018-11-20T13:03:53Z
dc.date.accessioned2022-10-15T07:50:23Z
dc.date.available2018-11-20T13:03:53Z
dc.date.available2022-10-15T07:50:23Z
dc.date.created2018-11-20T13:03:53Z
dc.date.issued2017-10
dc.identifierRevollo Sarmiento, Natalia Veronica; Delrieux, Claudio Augusto; Vessel and oil spill early detection using COSMO satellite imagery; Society of Photo-Optical Instrumentation Engineers; Spie; 10422:; 10-2017; 1-9
dc.identifier0277-786X
dc.identifierhttp://hdl.handle.net/11336/64690
dc.identifierCONICET Digital
dc.identifierCONICET
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4362377
dc.description.abstractOil spillage is one of the most common sources of environmental damage in places where coastal wild life is found in natural reservoirs. This is especially the case in the Patagonian coast, with a littoral more than 5000 km long and a surface above a million and half square km. In addition, furtive Ïshery activities in Argentine waters are depleting the food supplies of several species, altering the ecological equilibrium. For this reason, early oil spills and vessel detection is an imperative surveillance task for environmental and governmental authorities. However, given the huge geographical extension, human assisted monitoring is unfeasible, and therefore real time remote sensing technologies are the only operative and economically feasible solution. In this work we describe the theoretical foundations and implementation details of a system speciÏcally designed to take advantage of the SAR imagery delivered by two satellite constellations (the SAOCOM mission, developed by the Argentine Space Agency, and the COSMO mission, developed by the Italian Space Agency), to provide real-time detection of vessels and oil spills. The core of the system is based on pattern recognition over a statistical characterization of the texture patterns arising in the positive and negative conditions (i.e., vessel, oil, or plain sea surfaces). Training patterns were collected from a large number of previously reported contacts tagged by experts in the National Commission on Space Activities (CONAE). The resulting system performs well above the sensitivity and speciÏcity of other avalilable systems.
dc.languageeng
dc.publisherSociety of Photo-Optical Instrumentation Engineers
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/https://dx.doi.org/10.1117/12.2279545
dc.relationinfo:eu-repo/semantics/altIdentifier/url/https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10422/2279545/Vessel-and-oil-spill-early-detection-using-COSMO-satellite-imagery/10.1117/12.2279545.short
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectIMAGE PROCESSING
dc.subjectOIL SPILL DETECTION
dc.subjectPIXEL PROTOTYPES
dc.subjectSAR IMAGERY
dc.subjectSTATISTICAL INFERENCE
dc.subjectVESSEL DETECTION
dc.titleVessel and oil spill early detection using COSMO satellite imagery
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:ar-repo/semantics/artículo
dc.typeinfo:eu-repo/semantics/publishedVersion


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