An Event‐driven Spatiotemporal Data Model (E‐ST) Supporting Dynamic Expression and Simulation of Geographic Processes |
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| Authors: | Xiaolong Li Jiansi Yang Xuefeng Guan Huayi Wu |
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| Institution: | 1. State Key Laboratory, Wuhan University;2. Faculty of Geomatics, East China Institute of Technology;3. School of Urban Design, Wuhan University |
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| Abstract: | The wide use of various sensors makes real‐time data acquisition possible. A new spatiotemporal data model, the Event‐driven Spatiotemporal Data Model (E‐ST), is proposed to dynamically express and simulate the spatiotemporal processes of geographic phenomena. In E‐ST, a sensor object is introduced into the model as a flexible real‐time data source. An event type that is generating and driving conditions is registered into a geographic object, so an event can not only express spatiotemporal change in a geographic object, but also drive spatiotemporal change in some geographic objects. As a dynamic GIS data model, the E‐ST has five characteristics – Temporality and Spatiality, Real‐time, Extendability, Causality, and Realizability. Described and realized in UML, a test‐case deployment demonstrating the impact of urban waterlogging on traffic confirms that a spatiotemporal change process in a geographic phenomena is expressed and simulated by this model. Summarizing this work, four directions for future research are outlined. |
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