Spatial-temporal database model based on geodatabase

Hongmei Zhu; Yu Luo

doi:10.1117/12.838541

15 October 2009 Spatial-temporal database model based on geodatabase

Hongmei Zhu, Yu Luo

Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 74922Q (2009) https://doi.org/10.1117/12.838541
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China

Abstract

Entities in the real world have non-spatial attributes, as well as spatial and temporal features. A spatial-temporal data model aims at describing appropriately these intrinsic characteristics within the entities and model them on a conceptual level so that the model can present both static information and dynamic information that occurs over time. In this paper, we devise a novel spatial-temporal data model which is based on Geodatabase. The model employs object-oriented analysis method, combining object concept with event. The entity is defined as a feature class encapsulating attributes and operations. The operations detect change and store the changes automatically in a historic database in Geodatabase. Furthermore, the model takes advantage of the existing strengths of the relational database at the bottom level of Geodatabase, such as trigger and constraint, to monitor events on the attributes or locations and respond to the events correctly. A case of geographic database for Kunming municipal sewerage geographic information system is implemented by the model. The database reveals excellent performance on managing data and tracking the details of change. It provides a perfect data platform for querying, recurring history and predicting the trend of future. The instance demonstrates the spatial-temporal data model is efficient and practicable.

Citation Download Citation

Hongmei Zhu and Yu Luo "Spatial-temporal database model based on geodatabase", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74922Q (15 October 2009); https://doi.org/10.1117/12.838541

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