Using Google Earth in Marine Research and Operational Decision Support

Jonathan D Blower ¹, Daniel Bretherton ¹, Keith Haines ¹, Chunlei Liu ¹, Chris Rawlings ², Adit Santokhee ¹, Ian Smith <sup>2

1</sup>Reading e-Science Centre, University of Reading, ESSC, Harry Pitt Building, 3 Earley Gate, Whiteknights, Reading OX14 5DJ, United Kingdom
²BMT Cordah Ltd, Grove House, Meridians Cross, Ocean Village, Southampton SO14 3TJ, United Kingdom

A key advantage of Virtual Globes (``geobrowsers'') such as Google Earth is that they can display many different geospatial data types at a huge range of spatial scales. In this demonstration and poster display we shall show how marine data from disparate sources can be brought together in a geobrowser in order to support both scientific research and operational search and rescue activities. We have developed the Godiva2 interactive website for browsing and exploring marine data, mainly output from supercomputer analyses and predictions of ocean circulation. The user chooses a number of parameters (e.g. sea temperature at 100m depth on 1st July 2006) and can load an image of the resulting data in Google Earth. Through the use of an automatically-refreshing NetworkLink the user can explore the whole globe at a very large range of spatial scales: the displayed data will automatically be refreshed to show data at increasingly fine resolution as the user zooms in.

This is a valuable research tool for exploring these terabyte-scale datasets. Many coastguard organizations around the world use SARIS, a software application produced by BMT Cordah Ltd., to predict the drift pattern of objects in the sea in order to support search and rescue operations. Different drifting objects have different trajectories depending on factors such as their buoyancy and windage and so a computer model, supported by meteorological and oceanographic data, is needed to help rescuers locate their targets. We shall demonstrate how Google Earth is used to display output from the SARIS model (including the search target location and associated error polygon) alongside meteorological data (wind vectors) and oceanographic data (sea temperature, surface currents) from Godiva2 in order to support decision-making. We shall also discuss the limitations of using Google Earth in this context: these include the difficulties of working with time-dependent data and the need to access data securely.


URL:
http://lovejoy.nerc-essc.ac.uk:8080/Godiva2/