Title :
Spatio-temporal Knowledge Discovery in Very Large METOC Data Sets
Author :
Marks, D. ; Ioup, E. ; Sample, J. ; Abdelguerfi, M. ; Qaddoura, F.
Author_Institution :
Geospatial Intell., Naval Res. Lab., Stennis Space Center, MS, USA
Abstract :
A system allowing for the efficient processing and viewing of dense METOC data sets stored in Network Common Data Format (netted) files is developed using advanced bitmap indexing. A method for netted data extraction and bitmap index creation is presented. Efficient geospatial range and pseudo-KNN queries are implemented. A two step filtering algorithm is shown to greatly enhance the speed of these geospatial queries, allowing for extremely efficient processing of the netted data.
Keywords :
data mining; geography; learning (artificial intelligence); pattern clustering; query processing; spatiotemporal phenomena; very large databases; bitmap indexing; geospatial range; netted data extraction; network common data format; pseudo-KNN queries; spatio-temporal knowledge discovery; two step filtering algorithm; very large METOC data sets; Animation; Filtering algorithms; Geospatial analysis; Indexing; Three dimensional displays; METOC; bitmap indexing; geospatial processing; netCDF;
Conference_Titel :
Network and System Security (NSS), 2010 4th International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4244-8484-3
Electronic_ISBN :
978-0-7695-4159-4
DOI :
10.1109/NSS.2010.61
