Integrating Google Maps/Earth Into an Automated Oil Spill Forecast System
Abstract
An automated method for visualizing oil spill forecasts using Google Maps and Google Earth has been integrated into a Hydrodynamic and Oil Spill Python (HyosPy) modeling system. HyosPy downloads wind and tide observations and forecasts, runs a hydrodynamic model (the Semi-Implicit Eulerian Lagrangian Finite Element), links to an oil spill model (General NOAA Operational Modeling Environment), and visualizes the predicted spill trajectories. Using object-oriented approaches with Python code, HyosPy can run multiple instances of the hydrodynamic and oil spill models to provide a set of multiple predicted spill tracks controlled by different wind and tide forecasts. Automation of HyosPy allows the hydrodynamic model to be continuously running on a server so that hydrodynamic forecasts are immediately available in the event of a spill. Once the size, location, and time of the oil spill are provided to the system, no further human intervention is necessary. Google Maps/Earth visualization methods employ JavaScript tools and Keyhole Markup Language files to provide rapid display and animation in Web browsers of Java-capable devices. HyosPy is designed with a loosely coupled architecture to permit easy update and adaptation to different models and data sources.
An automated method for visualizing oil spill forecasts using Google Maps and Google Earth has been integrated into a Hydrodynamic and Oil Spill Python (HyosPy) modeling system. HyosPy downloads wind and tide observations and forecasts, runs a hydrodynamic model (the Semi-Implicit Eulerian Lagrangian Finite Element), links to an oil spill model (General NOAA Operational Modeling Environment), and visualizes the predicted spill trajectories. Using object-oriented approaches with Python code, HyosPy can run multiple instances of the hydrodynamic and oil spill models to provide a set of multiple predicted spill tracks controlled by different wind and tide forecasts. Automation of HyosPy allows the hydrodynamic model to be continuously running on a server so that hydrodynamic forecasts are immediately available in the event of a spill. Once the size, location, and time of the oil spill are provided to the system, no further human intervention is necessary. Google Maps/Earth visualization methods employ JavaScript tools and Keyhole Markup Language files to provide rapid display and animation in Web browsers of Java-capable devices. HyosPy is designed with a loosely coupled architecture to permit easy update and adaptation to different models and data sources.
Keywords: Google/Maps/Earth; automated; hydrodynamic model; oil spill model; oil spill prediction
Document Type: Research Article
Publication date: July 1, 2014
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