Date of Award

Fall 2011

Document Type


Degree Name

Master of Science (MS)


Computational Modeling & Simulation Engineering


Modeling and Simulation

Committee Director

Yuzhong Shen

Committee Member

Frederic D. McKenzie

Committee Member

Jiang Li

Call Number for Print

Special Collections LD4331.E58 L39 2011


For the persons who live near and travel the waters of the Chesapeake Bay, the data provided by the Chesapeake Bay Operational Forecast System (CBOFS) is invaluable. The information provided includes measurements and forecasts of surface wind velocity, water current velocity, salinity levels, water level, and temperature. Currently, this information is freely available on the CBQ_FS website hosted by the National Oceanographic and Atmospheric Administration (NOAA). It is offered as Nowcast, measured data, and Forecast data and is visualized using 2D images which describe a subset of the data in an easy to read chart. However, if the data were made available in a 3D environment, it would not only provide viewers with the general information currently available on the CBOFS website, but it would also provide users with a means to explore the data in the rich context of the surrounding environment. Viewers would have the ability to look at the data from any viewpoint, zoom in to see individual markers, and receive actual measurements in moments. This would considerably increase the use of the data measured by CBOFS as it would allow those who rely on this information to still receive the same data in a similar format, but it would also provide those interested in the Chesapeake Bay a means to learn more about the bay and how it functions under the water's surface.

This thesis proposes a framework for developing interactive visualizations of CBOFS data in Google Earth by exporting the CBOFS data into KML files which may be loaded into Google Earth from a standalone application or web plugin. Generation of these KML files involves retrieving the data files provided from OPeNDAP servers which host the CBOFS data files in NetCDF format. The pertinent raw data is then extracted from these data files using the Unidata Java library. The raw data is further processed based on the . grids utilized by CBOFS, and different visualization methods are employed to visualize different CBOFS variables. The final visualization results are then converted to KML files for efficient rendering in Google Earth. Finally, the KML files are organized into a carefully designed hierarchical structure and archived on a server for easy retrieval by the website designed to display the CBOFS data using Google Earth. The proposed framework provides several advantages over the current CBOFS visualization at the NOAA website: 1) it produces visualizations that are not available in the current CBOFS visualization; 2) it produces visualizations with resolution and accuracy much higher than that of the current CBOFS visualization; and 3) it provides users interactive capabilities that essentially do not exist in the current CBOFS visualization. Researchers, educators, students, and the general public will benefit greatly from the proposed framework.


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