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dc.contributor.advisorFuentes, Gabriel Moises
dc.contributor.authorJacobsen, Daniel D.
dc.contributor.authorHagen, Theodor W.
dc.date.accessioned2024-05-15T09:10:25Z
dc.date.available2024-05-15T09:10:25Z
dc.date.issued2023
dc.identifier.urihttps://hdl.handle.net/11250/3130501
dc.description.abstractThis master´s thesis investigates the ability of AIS data to detect suspected dark tankers in Russian ports and waters in light of the ongoing Russian and Ukranian conflict. The thesis aims to serve as a stepping stone between AIS data and satellite data in detecting dark tankers and show the possibilities and limitations of AIS data. By employing a geospatial analysis approach, which includes polygon and hexagonal tiling, the study narrows the focus to specific geographic regions that exhibit potential signs of suspicious activities. The methodology involves an extensive filtering process to scrutinize tanker behavior, effectively reducing the scope of the investigation to 14,3 percent of the tanker fleet. While the model demonstrates success in flagging potential dark tankers, the intrinsic constraints of AIS data mean that conclusive evidence of illicit activities, cannot be ascertained without the corroborative power of satellite data. Additionally, the thesis undertakes a secondary empirical analysis to investigate the impact of the $60 price cap, set on December 5, 2022, on Russian port activities. The findings indicate a notable uptick in operations and a strategic pivot towards eastern Russia. This study also explores the intricate ownership structures of the vessels in question, shedding light on the complexities of maritime operations within a sanctioned environment.en_US
dc.language.isoengen_US
dc.subjectfinanceen_US
dc.titleEmpirical Analysis of AIS Data‘s Ability to Detect Suspected Dark Oil Tankers in Russian Ports and Waters : An analysis in light of the Russian and Ukrainian conflicten_US
dc.typeMaster thesisen_US
dc.description.localcodenhhmasen_US


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