Thematic Data Index Construction Based on Urban Data

Article Preview

Abstract:

The paper is focused on these thematic data index construction, and puts forward a kind of category data indexes for rapid queries for urbanization thematic data index. The corresponding metadata tables could be constructed as non-spatial data are stored in the binary format. This aim is to classify the data by the metadata information and to establish the classified index respectively for the attribute data. The experiments confirmed that the proposed the category index can create urban thematic data index, and can quickly query attribute data needed.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

596-600

Citation:

Online since:

September 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Bömelburg, J., ATKIS-Datenintegration. Das Geoinformationssystem ATKIS und seine Nutzung in Wirtschaft and Verwaltung. 3. AdV-Symposium ATKIS, Koblenz (pp.199-204). (1996).

DOI: 10.26643/gis.v12i1.5207

Google Scholar

[2] Koch, C., Data Integration against Multiple Evolving Autonomous Schemata, PhD thesis, Technical University (TU)Vienna. (2001).

Google Scholar

[3] Dadam, P., Verteilte Datenbanken und Client/Server-Systeme. Grundlagen, Konzepte und Realisierungsformen, Berlin: Springer, (1996).

DOI: 10.1007/978-3-642-61472-9_3

Google Scholar

[4] Gabay, Y. & Doytsher, Y. Automatic Feature Correction in Merging Line Maps. ACSM/ASPRS Annual Convention & Exposition Technical Papers, (pp.404-411), Charlotte, North Carolina. (1995).

Google Scholar

[5] Walter, V. & Fritsch, D. Matching Strategies for Integration of Spatial Data from Different Sources. International Workshop on Dynamic and Multi-Dimensional GIS, (pp.215-228), Hong Kong. (1997).

Google Scholar

[6] Sester, M., Anders, K. -H. & Walter, V. Linking Objects of Different Spatial Data Sets by Integration and Aggregation. Geoinformatica 2(4), 335-357. (1998).

Google Scholar

[7] Weibel, R. & Jones, C. B. Computational Perspectives on Map Generalization. Geoinformatica 2(4), 307-314. (1998).

Google Scholar

[8] Lamy, S., Ruas, A., Demazeau, Y., Jackson, M., Mackaness, W. A. & Weibel, R. The Application of Agents in Automated Map Generalisation. 19th Int. Cartographic Conference, Ottawa, Canada (pp.160-169). (1999).

Google Scholar

[9] Cecconi, A. & Weibel, R. Map Generalization for On-demand Mapping. GIM International 15(5), 12-15. (2001).

Google Scholar

[10] Rudolf Bayer, Edward M. McCreight. Organization and Maintenance of Large Ordered Indices [J]. Acta Informatica 1, 1972: 173~189.

DOI: 10.1007/bf00288683

Google Scholar

[11] Carter J., M. Wegman. Universal classes of hash functions [J]. Journal of Computer and System Sciences, 1977, 18 (2): 143~154.

DOI: 10.1016/0022-0000(79)90044-8

Google Scholar

[12] Chan C., Y. Ioannidis. Bitmap index design and evaluation [J]. ACM SIGMOD Record, 1998, 27(2): 355~366.

DOI: 10.1145/276305.276336

Google Scholar