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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
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ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  3/2009 - 2

 HIGHLY CITED PAPER 

GEOBARN: A Practical Grid Geospatial Database System

HUANG, Z. See more information about HUANG, Z. on SCOPUS See more information about HUANG, Z. on IEEExplore See more information about HUANG, Z. on Web of Science, FANG, Y. See more information about  FANG, Y. on SCOPUS See more information about  FANG, Y. on SCOPUS See more information about FANG, Y. on Web of Science, XIE, X. See more information about  XIE, X. on SCOPUS See more information about  XIE, X. on SCOPUS See more information about XIE, X. on Web of Science, PAN, M. See more information about PAN, M. on SCOPUS See more information about PAN, M. on SCOPUS See more information about PAN, M. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (939 KB) | Citation | Downloads: 1,172 | Views: 4,616

Author keywords
distributed database, grid computing, GIS

References keywords
data(12), spatial(6), information(6), geospatial(6), system(4), knowledge(4), distributed(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2009-10-26
Volume 9, Issue 3, Year 2009, On page(s): 7 - 11
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2009.03002
Web of Science Accession Number: 000271872000002
SCOPUS ID: 77954684261

Abstract
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Full text preview
Recently, more and more geospatial data are generated and distributed with the promising data acquirement techniques like satellite imaging and digital cartography. So, it is an important issue to effectively make use of these huge geospatial data resources. This means that effective data processing technologies need to be developed to support distributed query and analysis operations onto the distributed resources. The emergence of grid computing technology offers a good solution to accomplish this goal. To combine the grid computing technique with geospatial database we design and implement a GGDS (Grid Geospatial Database System) prototype named GEOBARN. Key modules and detailed implementation methods of GEOBARN are discussed in this paper. By using the GEOBARN system, both reliable data management and effective distributed geospatial query can be achieved.


References | Cited By  «-- Click to see who has cited this paper

[1] M. Erwig, M. Schneider and R.H. Guting, "Temporal Objects for Geospatial Data Models and a Comparison of Their Representations", Proceedings of the Workshops on Data Warehousing and Data Mining (1998)

[2] Y. Xue, A.P. Cracknell and H.D. Guo, "Telegeoprocessing: The integration of remote sensing, geographic information system (GIS), global positioning system (GPS) and telecommunication", International Journal of Remote Sensing. 23: 1851-1893 (2002)
[CrossRef] [Web of Science Times Cited 22] [SCOPUS Times Cited 35]


[3] Z. Shen, J. Luo and C. Zhou, "Architecture design of grid GIS and its applications on image processing based on LAN", Information Sciences. 166:1-17 (2004)
[CrossRef] [Web of Science Times Cited 28] [SCOPUS Times Cited 46]


[4] I. Foster, C. Kesselman, J.M. Nick and S. Tuecke "Grid services for distributed system integration", Computer. 6:37-46 (2002)
[CrossRef] [Web of Science Times Cited 637] [SCOPUS Times Cited 1023]


[5] "The Globus Project Argonne National Laboratory USC Information Sciences Institute: Grid Architecture", Available from: http://www.globus.org

[6] N. Giannadakis, A. Rowe, M. Ghanem, Y. K. Guo, "InfoGrid: providing information integration for knowledge discovery", Information Sciences. 155:199-226 (2003)
[CrossRef] [Web of Science Times Cited 22] [SCOPUS Times Cited 28]


[7] C.C. Aggarwal, "A framework for diagnosing changes in evolving data streams", Proceedings of the 2003 ACM SIGMOD international conference on Management of data (2003)
[CrossRef]


[8] H. Cao, O. Wolfson and G. Trajcevski, "Geospatial data reduction with deterministic error bounds", Proceedings of the 2003 joint workshop on Foundations of mobile computing (2003)

[9] M. J. Egenhofer, "Spatial SQL, A query and presentation language", IEEE Transactions on Knowledge and Data Engineering. 6(1): 86-95 (1994)
[CrossRef] [Web of Science Times Cited 157] [SCOPUS Times Cited 228]


[10] S.K. Harms, J. Deogun, S. Goddard, "Building knowledge discovery into a geo-spatial decision support system", Proceedings of the 2003 ACM symposium on Applied computing (2003)
[CrossRef]


[11] C.R. Lin, K.H. Liu, M.S. Chen, "Dual Clustering: Integrating Data Clustering over Optimization and Constraint Domains", IEEE Transactions on Knowledge and Data Engineering. 17(5): 39-48 (2005)
[CrossRef] [Web of Science Times Cited 34] [SCOPUS Times Cited 57]


[12] K. Hornsby, "Workshop Report - International Workshop on Temporal, Spatial, and Geospatial Data Mining", Proceedings of the First International Workshop on Temporal, Spatial, and Geospatial Data Mining (2000)

[13] Z. Huang, Y. Fang, B. Chen, D. Yin and X. Peng, "A Global View Oriented Approach to Directory Management in Distributed Spatial Database", Proceedings of SPIE-The International Society for Optical Engineering, Vol.6418, GNSS and Integrated Geospatial Applications. 64181O (2006)
[CrossRef] [Web of Science Record] [SCOPUS Times Cited 3]


[14] L. Savary, T. Wan and K. Zeitouni, "Geospatial Data Warehouse Design for Human Activity Pattern Analysis", Proceedings of the Database and Expert Systems Applications, 15th International Workshop (2004)

[15] Z. Huang, B. Chen and Y. Fang, "An SQL Transformation Based Optimization Algorithm of Distributed Spatial Query", High Technology Letters. 17(10): 1013-1018(2007)

[16] Z. Huang, X. Peng and K. Zhang. "An Approach to Geographic SQL Global Parsing under Distributed Computation Circumstance", Geography and Geographic Information Science. 21(3): 18-21(2006)



References Weight

Web of Science® Citations for all references: 900 TCR
SCOPUS® Citations for all references: 1,420 TCR

Web of Science® Average Citations per reference: 53 ACR
SCOPUS® Average Citations per reference: 84 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2021-06-09 13:24 in 68 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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