Title :
Application of DDDAS in marine oil spill management: A new framework combining multiple source remote sensing monitoring and simulation as a symbiotic feedback control system
Author :
Yao Li ; Lizhe Wang ; Lajiao Chen ; Yan Ma ; Xiaomin Zhu ; Bin Chu
Author_Institution :
Beijing Univ. of Technol., Beijing, China
Abstract :
Marine oil spills is one of the most serious sea pollution which has a horrible effect on environment, economy, and quality of life for coastal inhabitants. How to reduce the risk of oil spill disasters has become one of the principal problems faced with marine environment management. Oil spill observation and spill processes simulation are two main parts for oil spill accident controlling and management. Traditionally, the oil spill information detection and spill simulation is disjoined without any feedback. The modeling approach is all conducted with fixed structure and static data input while the observation system is always static with fixed monitoring scheme. In such a circumstance, neither the observation system nor the simulation can provide highly accurate information. This paper propose a new framework combining oil spill monitoring and simulation as a symbiotic feedback control system based on the theory of Dynamic Data Drive Application System (DDDAS), a new paradigm dynamically integrated simulations, measurements, and applications. The numerical oil spill model can accepts real time data from remote sensing monitoring which assure modeling a more accurate and more reliable outcomes. Multiple simulations will be executed with different remote sensing monitoring scheme and the feedback from simulation guide and determine how to gather the data. For mathematical modeling of the DDDAS based marine oil spill management system, we built a multi-stage optimization model. Such system could promise more accurate prediction and more reliable outcomes with real time oil spill input, which will improve modeling technologies, advance prediction capabilities of simulation systems, and enhance oil spill monitoring.
Keywords :
control systems; disasters; marine pollution; oil pollution; remote sensing; water quality; DDDAS application; DDDAS based marine oil spill management system; DDDAS theory; accurate modeling; accurate prediction; advance prediction capabilities; coastal inhabitants; dynamic application integration; dynamic data drive application system theory; dynamic measurement integration; dynamic simulation integration; economy effect; enhance oil spill monitoring; environment effect; fixed monitoring scheme; fixed structure; highly accurate information; improve modeling technologies; life quality effect; marine environment management; marine oil spill management; mathematical modeling; modeling approach; multiple simulations; multiple source remote sensing monitoring; multiple source remote sensing simulation; multistage optimization model; numerical oil spill model; observation system; oil spill accident controlling; oil spill accident management; oil spill disaster risk reduction; oil spill information detection; oil spill monitoring; oil spill observation; oil spill simulation; real time data; real time oil spill input; reliable modeling outcomes; remote sensing monitoring; remote sensing monitoring scheme; sea pollution; simulation guide feedback; simulation systems; spill process simulation; static data input; symbiotic feedback control system; Data models; Mathematical model; Monitoring; Numerical models; Real-time systems; Remote sensing; Satellites; Dynamic data driven application system; Marine oil spill; Remote sensing;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4799-1114-1
DOI :
10.1109/IGARSS.2013.6723842