Review of Spatial Indexing Techniques for Large Urban Data Management

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.