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Remote Sens. 2015, 7(6), 7105-7125;

A Dynamic Remote Sensing Data-Driven Approach for Oil Spill Simulation in the Sea

Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
University of Chinese Academy of Sciences, Beijing 100049, China
School of Computer Science, China University of Geoscience, Wuhan 430074, China
Space Science and Engineering Center, University of Wisconsin-Madison, Madison, WI 53706, USA
Author to whom correspondence should be addressed.
Academic Editors: Parth Sarathi Roy and Prasad S. Thenkabail
Received: 20 January 2015 / Revised: 10 May 2015 / Accepted: 15 May 2015 / Published: 29 May 2015
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In view of the fact that oil spill remote sensing could only generate the oil slick information at a specific time and that traditional oil spill simulation models were not designed to deal with dynamic conditions, a dynamic data-driven application system (DDDAS) was introduced. The DDDAS entails both the ability to incorporate additional data into an executing application and, in reverse, the ability of applications to dynamically steer the measurement process. Based on the DDDAS, combing a remote sensor system that detects oil spills with a numerical simulation, an integrated data processing, analysis, forecasting and emergency response system was established. Once an oil spill accident occurs, the DDDAS-based oil spill model receives information about the oil slick extracted from the dynamic remote sensor data in the simulation. Through comparison, information fusion and feedback updates, continuous and more precise oil spill simulation results can be obtained. Then, the simulation results can provide help for disaster control and clean-up. The Penglai, Xingang and Suizhong oil spill results showed our simulation model could increase the prediction accuracy and reduce the error caused by empirical parameters in existing simulation systems. Therefore, the DDDAS-based detection and simulation system can effectively improve oil spill simulation and diffusion forecasting, as well as provide decision-making information and technical support for emergency responses to oil spills. View Full-Text
Keywords: DDDAS; remote sensing; oil spill; detection; simulation 1. DDDAS; remote sensing; oil spill; detection; simulation 1.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Yan, J.; Wang, L.; Chen, L.; Zhao, L.; Huang, B. A Dynamic Remote Sensing Data-Driven Approach for Oil Spill Simulation in the Sea. Remote Sens. 2015, 7, 7105-7125.

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