Review of Spatial Indexing Techniques for Large Urban Data Management

Suhaibah Azri, Uznir Ujang, François Anton, Darka Mioc, Alias Abdul Rahman

Research output: Contribution to conferencePaperResearchpeer-review


Pressure on land development in urban areas causes progressive efforts in spatial planning and management. The physical expansion of urban areas to accommodate rural migration implies a massive impact to social, economical and political situations of major cities. Most of the models used in managing urban areas are moving towards sustainable urban development in order to fulfill current necessities while preserving the resources for future generations. However, in order to manage large amounts of urban spatial data, an efficient spatial data constellation method is needed. With the ease of three dimensional (3D) spatial data usage in urban areas as a new source of data input, practical spatial data indexing is necessary to improve data retrieval and management. Current two dimensional (2D) spatial indexing approaches seem not applicable to the current and future spatial developments. Therefore, the objective of this paper is to review existing spatial data indexing approaches for managing large urban area datasets. Each approach will be reviewed and discussed according to the current spatial data scenarios. In addition, a 3D spatial data indexing method will be discussed as an alternative for organizing 3D spatial data.
Original languageEnglish
Publication date2013
Number of pages23
Publication statusPublished - 2013
EventInternational Symposium & Exhibition on Geoinformation - Universiti Teknologi Malaysia , Kuala Lumpur, Malaysia
Duration: 24 Sep 201325 Sep 2013


WorkshopInternational Symposium & Exhibition on Geoinformation
LocationUniversiti Teknologi Malaysia
CityKuala Lumpur
Internet address


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  • Universiti Teknologi Malaysia

    Francesc/François Antón Castro (Visiting researcher)

    30 May 201329 Aug 2013

    Activity: Visiting an external institutionVisiting another research institution

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