Spatial Databases,10.1002/9780470050118.ecse408,Vijay Gandhi,James M. Kang,Shashi Shekhar

Spatial Databases   (Citations: 13)
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Spatial database research has continued to advance greatly since three decades ago, addressing the growing data management and analysis needs of spatial applications. This research has produced a taxonomy of models for space, conceptual models, spatial query languages and query processing, spatial file organization and indexes, and spatial data mining. However, emerging needs for spatial database systems include the handling of 3D spatial data, temporal dimension with spatial data, and spatial data visualization. In addition, the rise of new systems such as sensor networks and multi-core processors is likely to have an impact in spatial databases. The goal of this paper is to provide a broad overview of the recent advancements in spatial databases and research needs in each area.
Published in 2008.
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    • ...The selection of spatial data mining algorithms is relative to the space knowledge or model that Mine Safety needed . In general, spatial data mining includes three main mode : (1)classification and prediction models; (2)clustering and isolation points detection mode;(3) spatial association rules.[4]...

    Shao Chang'anet al. The Research on Safety Monitoring System of Coal Mine Based on Spatial...

    • ...As another example, spatial data mining tasks may heavily access correlated data due to the autocorrelation among spatial data indicating events of interest such as traffic patterns or chemical/disease dispersion [18, 7]. Further, they can access different sets of hot correlated data over time...
    • ...As discussed before, spatial and temporal data are auto-correlated [18, 7]. Also, more end-users may request to access traffic and weather data in a congested area...
    • ...Spatial and temporal databases focus on developing efficient spatial and temporal models and query processing techniques [18, 4]. Recently, the integration of spatial and temporal models is actively studied [7]...

    Kyoung-don Kanget al. Adaptive Data Replication for Load Sharing in a Sensor Data Center

    • ...It is the process of discovering interesting and previously unknown, but potentially useful patterns from spatial databases [8, 9]. Extracting patterns of interest from spatial datasets is more difficult than extracting the corresponding patterns from traditional numeric and categorical data due to the complexity of spatial data types, spatial relationships and spatial autocorrelation [10]...

    Fadi K. Deebet al. A methodology for discovering spatial co-location patterns

    • ...Definition 1: For each scatter point on the combined surfaces, its surface domain set is the scatter point set of its neighbour according to spatial relation matrix NN , where relationships are distance or adjacency [8]...

    Zhanquan Wanget al. Extracting Characteristic Points of the Surfaces without a Support Thr...

    • ...As pointed out in [10], the cost of fully transcribing spatial data into a transactional representation can, in some cases, be more expensive than the mining of the colocations, but as a full representation is necessary to accurately add the features representing absent and multiple items, a solution to this in the current representation may be problematic...

    Robert Munroet al. Complex Spatial Relationships

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