1. SAR observation and model tracking of an oil spill event in coastal waters.
- Author
-
Cheng, Yongcun, Li, Xiaofeng, Xu, Qing, Garcia-Pineda, Oscar, Andersen, Ole Baltazar, and Pichel, William G.
- Subjects
SYNTHETIC aperture radar ,OIL spills ,ARTIFICIAL neural networks ,ALGORITHMS ,MATHEMATICAL models ,TERRITORIAL waters ,SIMULATION methods & models - Abstract
Abstract: Oil spills are a major contributor to marine pollution. The objective of this work is to simulate the oil spill trajectory of oil released from a pipeline leaking in the Gulf of Mexico with the GNOME (General NOAA Operational Modeling Environment) model. The model was developed by NOAA (National Oceanic and Atmospheric Administration) to investigate the effects of different pollutants and environmental conditions on trajectory results. Also, a Texture-Classifying Neural Network Algorithm (TCNNA) was used to delineate ocean oil slicks from synthetic aperture radar (SAR) observations. During the simulation, ocean currents from NCOM (Navy Coastal Ocean Model) outputs and surface wind data measured by an NDBC (National Data Buoy Center) buoy are used to drive the GNOME model. The results show good agreement between the simulated trajectory of the oil spill and synchronous observations from the European ENVISAT ASAR (Advanced Synthetic Aperture Radar) and the Japanese ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array L-band Synthetic Aperture Radar) images. Based on experience with past marine oil spills, about 63.0% of the oil will float and 18.5% of the oil will evaporate and disperse. In addition, the effects from uncertainty of ocean currents and the diffusion coefficient on the trajectory results are also studied. [Copyright &y& Elsevier]
- Published
- 2011
- Full Text
- View/download PDF