Improving Public Understanding of Catastrophic Events

Improving Public Understanding of Catastrophic EventsPI: Robert Moorhead

DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited.

Team Members

Phil Amburn, GRI, Associate Research ProfessorDerek Irby, GRI, Research AssociateJean Mohammadi-Aragh, GRI, Research Associate Robert Moorhead, GRI, ECE Dept., PIJibo Sanyal, ECE, PhD studentKequn Wu, CSE, PhD student Song Zhang, GRI, CSE Dept., Assistant Professor


Team EffortsGoogle EarthTarget Audience: Non-technical Public

Through a few simple mouse clicks on our web interface, a visitor can generate KML to investigate desired storm data in Google Earth - without ever writing a single line of KML. The web interface and Google Earth are platform independent.Triton IITarget Audience: Scientists

Triton II is a virtual realty demo that runs in MSUs VERTEX facility. It overcomes different grids to combine meteorological and oceanographic data in one program, allowing for the exploration of storms as they progress from the ocean to land.Evenly Spaced StreamlinesTarget Audience: Scientists and the Public

Evenly spaced streamlines are more than just prettier pictures; they ensure full coverage of all flow features, enabling a better understand of the flow from both a technical and non-technical point of view. Evenly spaced streamlines ensure majority, if not all, flow features are visible.vGeoTarget Audience: Scientists

We use vGeo in MSUs VERTEX facility to navigate and interact with time varying, three-dimensional worlds created from a multitude of data sets including satellite imagery (remote sensing) and MM5 Model Output (atmospheric circulation, e.g., hurricane data).* Highlighted at the 2008 NGI Annual Conference


Google Earth ExamplesGoogle Earth is already being used to visualize weather phenomena such as ocean currents, cloud cover, and flooding. However, the non-technical public, with no knowledge of programming or KML coding, is limited to visualizations someone else has already created.


Through a variety of drop down boxes, a visitor can select which data sets, variables, and visualization techniques they would like included in their KML. After selecting Build KML, the system generates their custom KML file which is previewed in Google Maps and can be loaded into Google Earth.


AGAVE: A GoogleEarth Automated Visualization EnvironmentExample: Hurricane Katrina and Hurricane Lili Tracks


AGAVE: A GoogleEarth Automated Visualization EnvironmentExample: Colored columns to indicate Storm Surge Height (based on FEMA High Water Marks)


AGAVE: A GoogleEarth Automated Visualization EnvironmentExample: Hurricane Katrina satellite imagery overlay, with hurricane path and points of interest.


Documents

Improving Public Understanding of Catastrophic Events