A Tool for Visualising Large Oceanographic, Atmospheric and GIS Datasets
John C. Anderson and Duke J. Hartman Makai Ocean Engineering, Inc. P.O. Box 1206, Kailua, HI 96734 USA • Web:
www.makai.com
This paper describes the development and main operational capabilities of Makai Voyager, a geospatially enabled software that can fuse and visualise large, multi-variable data sets that change
in space (x,y,z) and time (t) for weather phenomena such as precipitation patterns and typhoons. The new software has the ability to simultaneously visualise imagery, bathymetry/terrain, and true volumetric (voxel) data in a fully interactive geo-referenced mode. In addition to providing global coverage, a key feature of this software is the capability to interactively visualise large data sets while operating on a desktop PC.
Sensing the winds and weather has been important to man over the centuries. Many significant weather events have affected mankind over the years and the debate over the increasing frequency of extreme weather events is growing stronger. An early reference to the importance of the weather comes from the Chinese philosopher Sun Tsu, who once said, “Know yourself and know your enemy, and victory is guaranteed. Know the terrain and know the weather, and you will have total victory”. Recent flooding in Thailand and Pakistan has highlighted the requirement to continue to monitor and efficiently visualise weather patterns and phenomena.
Never before in history has there been more data collected from sensors deployed all over the globe for meteorological purposes. Data from these sensors are used in numerical models for oceanographic and meteorological studies in addition to many other applications. The size and complexity of data processed by these models has increased exponentially in recent years. Today it is common for simulations to produce gigabytes or terabytes of data containing multiple variables of interest that change in both space (x,y,z) and time (t). With an increasing demand on the processing and visualisation of these large data sets, meteorologists are facing a fundamental problem in how to efficiently and accurately manage and interpret the vast amount of dynamic oceanographic and atmospheric data being collected and modeled.
Until recently many scientific and meteorological activities were limited to using sub-sets of the data, increasing the possibility of missing important and critical information due to the lack of efficient tools to extract and visualise relevant features of these data sets. Furthermore, most data was, and often still is, being presented using sequences of multiple flat 2D images, which is a very inefficient and time consuming method to extract and analyse information. Therefore, it is critical that new technology be developed which can efficiently fuse and display a richer and more immersive representation of the data in order to improve understanding, whether it is for planning, modeling, simulation, or actual operations (e.g. incorporating real-time meteorological numerical models with GIS data on population centers to produce flash flood guidance and threat information).
In the last several years, efforts to develop better tools to fuse and visualise atmospheric data have been on-going. However, most of these tools are still limited in the amount of data they can load for analysis in an interactive mode. Systems that have the capability to render large data sets still rely on cluster and specialised hardware to run interactively and this has drastically limited their use by the general scientific community.
Processes, Integrates and Visualises data in a real-time 3D/4D viewer
Figure 1: Software combines visualisation of terrain/bathymetry, imagery, 3D/4D time dependent iso-surfaces and volume data, asset tracking, and a wide variety of GIS data; all in a complete geo-referenced environment.
Other well known, highly interactive software systems used to view large amounts of terrain and image data (e.g., Google Earth, Microsoft and Virtual Earth) and the true GIS software (e.g., ESRI and Intergraph products) are still not capable of displaying large scientific data sets, such as volumetric data, that change in time. They are restricted primarily to display imagery, terrain, and 3D objects. Many existing scientific programs were not designed to easily incorporate geo- referenced data such as large image files, elevation/bathymetry and the large number of commonly used GIS data.
Motivation and Design Specifications
In addition to the limitations mentioned for existing visualisation software packages, meteorologists are often forced to use a large variety of tools to pre-process their different data sets before they can input them into existing visualisation and GIS programs. The shortcomings in existing data fusion and visualisation technology motivated the creation of a single product that would eliminate most of the above limitations.
Over the last 5 years, Makai Ocean Engineering, with funding
AET October / November 2011
www.envirotech-online.com
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