Extracting spatio-temporal patterns from geoscience datasets
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 information system called QUEST to provide content-based acces...
Gespeichert in:
Hauptverfasser: | , , , , , , |
---|---|
Format: | Tagungsbericht |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | 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 information 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.< > |
---|---|
DOI: | 10.1109/VMV.1994.324983 |