Challenges and Critical Issues for Temporal GIS Research and Technologies

Challenges and Critical Issues for Temporal GIS Research and Technologies

May Yuan (University of Oklahoma, USA)
Copyright: © 2009 |Pages: 10
DOI: 10.4018/978-1-59140-995-3.ch019
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Temporal Geographic Information Systems (GIS) technology has been a top research subject since late the 1980s. Langran’s Time in Geographic Information Systems (Langran, 1992) sets the first milestone in research that addresses the integration of temporal information and functions into GIS frameworks. Since then, numerous monographs, books, edited collections, and conference proceedings have been devoted to related subjects. There is no shortage of publications in academic journals or trade magazines on new approaches to temporal data handling in GIS, or on conceptual and technical advances in spatiotemporal representation, reasoning, database management, and modeling. However, there is not yet a full-scale, comprehensive temporal GIS available. Most temporal GIS technologies developed so far are either still in the research phase (e.g., TEMPEST developed by Peuquet and colleagues at Pennsylvania State University in the United States) or with an emphasis on mapping (e.g., STEMgis developed by Discovery Software in the United Kingdom).
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Critical Issues

What constitutes a temporal GIS needs to be addressed from three perspectives: (1) database representation and management; (2) analysis and modeling; and (3) geovisualization and communication. There were at least four commercial “temporal GIS” available in 2005: DataLink; STEMgis; TerraSeer, and Temporal Analyst for ArcGIS. In addition, there are many open-source software for spatiotemporal visualization and analysis, such as STAR, UrbanSim, SLEUTH and ArcHydro. 1However, most of these systems were designed for certain application domains and only address the three temporal GIS aspects based on their identified applications. Building upon all of the recent conceptual and technological advances in temporal GIS, researchers are now well positioned to examine the big picture of temporal GIS development, address critical issues from all three perspectives, and envision the next generation of spatiotemporal information technologies.

Key Terms in this Chapter

Temporal GIS: Geographic information systems that are capable of managing, organizing, retrieving, analyzing, and modeling time-dependent spatial information.

Snapshot: Data captured instantly at a point in time. Most remote sensing imageries are considered snapshots, even though not all pixels are scanned at the same time.

Spatiotemporal Representation: Conceptual or physical frameworks in an information system to capture spatial and temporal properties of reality.

Geovisualization: Graphical presentations of geographic information or statistical summaries about properties and relationships in space and/or time.

Spatiotemporal Query: Information inquiries about geographic properties, behaviors, or relationships in space and time.

Cellular Automata: A spatiotemporal modeling technique in which a set of rules is applied to determine the state transitions of individual cells based on each cell’s current state and the states of its neighbors.

Agent-Based Model (ABM): A modeling technique with a collection of autonomous decision-making agents, each of which assesses its situation individually and makes decisions on the basis of a pre-set of rules. ABM is used to simulate land use land cover change, crowd behavior, transportation analysis and many other fine-scale geographic applications.

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