An Event‐driven Spatiotemporal Data Model (E‐ST) Supporting Dynamic Expression and Simulation of Geographic Processes. (14th November 2014)

• Record Type: Journal Article
• Authors: Li, Xiaolong; Yang, Jiansi; Guan, Xuefeng; Wu, Huayi
• Is Part Of: Transactions in GIS. Volume 18(2014)Supplement 1
• Page Start: 76
• Page End: 96
• Publication Date: 2014-11-14
• Subjects: Geographic information systems -- Periodicals; 910.285
• DOI: 10.1111/tgis.12127
• Languages: English
• ISSNs: 1361-1682

Abstract

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.