Summary:
Too much information often kills information. With the increasing number of satellites and their ever-increasing performance, new
tools must be made available to deal with this onslaught of data. We noticed that a number of computer graphics tools were largely
under-exploited to help scientists better interpret and find relevant information in large sets of data. A modern approach to run large
processes efficiently is the use of GPUs, but nowadays the emphasis is often put on the parallel processing of geospatial datasets
rather than focusing on their visualization. The main contributions of this paper is to consider geospatial data using GPU resources
for intermediate computation and visualization. Considering the increasing interest to interact with this data directly using Web
pages or Notebooks, this article presents tools allowing a program to run on the GPU and display the desired datacubes using the
WebGL API. The end goal is to display even large (i.e. 1024^3) datacubes rendered on the fly in real time on a PC. This paper
presents a range of models applicable to datacubes deployed in the context of terrestrial observation. Results show our models can
process large amounts of data and render them in real-time. All of these highly efficient rendering models are assembled together in
a toolbox dedicated to datacube visualization. In this paper we demonstrate an example of application using this toolbox to retrieve
raw data from a server, format it for local use with GPGPU, and render it with several innovative models.
KEY WORDS: Data Visualization, Data Cube, Earth Observation, Raycasting, 3D Rendering, WebGL, GLSL, Toolbox.
AUTHOR = {Muller, C. and Lestrade, A. and Marty, M. and Sadiku, A. and Neijt, J. and Voumard, Y. and Gobron, S.},
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