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Issue No.05 - September/October (2000 vol.20)
pp: 52-57
Data sets with large number of missing values pose a common problem because most standard scientific visualization algorithms fail when presented with incomplete cells. In this article we discuss the pros, cons, and pitfalls of the alternatives and present our experience in dealing with gridded data sets with missing or invalid scalar data. In our study we emphasized visualization methods that exploit the clustering pattern in the data. We applied our findings to data acquired from Nexrad (next generation radars) weather radars, which usually have no more than 3 to 4 percent of all possible cell points filled.
isosurface, contouring, volume ren-dering, sparse gridded datasets, NEXRAD.
Suzana Djurcilov, Alex Pang, "Visualizing Sparse Gridded Data Sets", IEEE Computer Graphics and Applications, vol.20, no. 5, pp. 52-57, September/October 2000, doi:10.1109/38.865880
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