Graduation Year

2018

Document Type

Thesis

Degree

M.S.C.S.

Degree Name

MS in Computer Science (M.S.C.S.)

Degree Granting Department

Computer Science and Engineering

Major Professor

Dmitry B. Goldgof, Ph.D.

Co-Major Professor

Kendra Daly, Ph.D.

Committee Member

Lawrence Hall, Ph.D.

Keywords

Shadowed Image Particle Profiling Evaluation Recorder (SIPPER), Plankton Image Classification and Extraction Software (PICES), Interactive Visualization Application (IVA), Interactive Statistical Analysis Application (ISAA)

Abstract

The Deepwater Horizon oil spill that started on April 20, 2010, in the Gulf of Mexico was the largest marine oil spill in the history of the petroleum industry. There was an unexpected and prolonged sedimentation event of oil-associated marine snow to the seafloor due to the oil spill. The sedimentation event occurred because of the coagulation process among oil associated marine particles. Marine scientists are developing models for the coagulation process of marine particles and oil, in order to estimate the amount of oil that may reach the seafloor along with marine particles. These models, used certain assumptions regarding the shape and the texture parameters of marine particles. Such assumptions may not be based on accurate information or may vary during and after the oil spill. The work performed here provided a quantitative analysis of the assumptions used in modeling the coagulation process of marine particles. It also investigated the changes in model parameters (shape and texture) during and after the Deepwater Horizon oil spill in different seasons (spring and summer). An Interactive Visualization Application was developed for data exploration and visual analysis of the trends in these parameters. An Interactive Statistical Analysis Application was developed to create a statistical summary of these parameter values.

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