Extracting Spatio-Temporal Patterns from Geoscience Datasets (1994) [11 citations — 4 self]
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author = {E. Mesrobian and R. R. Muntz and C. R. Mechoso and P. Stolorz and J. R. Santos and E. C. Shek and J. D. Farrara},
title = {Extracting Spatio-Temporal Patterns from Geoscience Datasets},
booktitle = {In Proc. IEEE Workshop on Visualization and Machine Vision},
year = {1994},
pages = {92--103},
publisher = {IEEE Computer Society}
}
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Abstract:
A major challenge facing geophysical science today is the unavailability of high-level analysis tools with which to study the massive amount of data produced by sensors or long simulations of climate models. We have developed a prototype system called QUEST to provide content-based access to massive datasets. QUEST employs workstations as well as teraFLOP computers to analyze geoscience data to produce spatial-temporal features that can be used as high-level indexes. Our first application area is global change climate modeling. In the initial prototype, the first features extracted are cyclones trajectories from the output of multi-year climate simulations produced by a General Circulation Model. We present an algorithm for cyclone extraction and illustrate the use of cyclone indexes to access subsets of GCM data for further analysis and visualization. 1 Introduction A critical challenge facing geophysical science today is the unavailability of high-level analysis tools with which to ...
