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GI_Forum 2018, Volume 6, Issue 1Journal for Geographic Information Science
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Verlag der Österreichischen Akademie der Wissenschaften Austrian Academy of Sciences Press
A-1011 Wien, Dr. Ignaz Seipel-Platz 2
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400 https://verlag.oeaw.ac.at, e-mail: verlag@oeaw.ac.at |
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DATUM, UNTERSCHRIFT / DATE, SIGNATURE
BANK AUSTRIA CREDITANSTALT, WIEN (IBAN AT04 1100 0006 2280 0100, BIC BKAUATWW), DEUTSCHE BANK MÜNCHEN (IBAN DE16 7007 0024 0238 8270 00, BIC DEUTDEDBMUC)
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GI_Forum 2018, Volume 6, Issue 1, pp. 16-33, 2018/06/22
Journal for Geographic Information Science
Research in transport, ecology, health and other fields stands to profit from an improved understanding of movement. As movement data availability improves, the need for appropriate movement data analysis increases. However, the limited support for modelling moving objects in GIS hampers data exploration and analysis. This paper discusses trajectory data models and their implementation in the open-source spatial database system PostGIS. We quantify the difference in performance between PostGIS default trajectory support, dedicated trajectory data models, and commonly used point-based data models. To the best of our knowledge, this is the first paper to evaluate PostGIS default trajectory support and compare it to a proposed dedicated trajectory data type from the literature. Our experiments include computing trajectory duration and length, temporal and spatial filters, extracting positions at a certain time, and visualizing trajectories in desktop GIS. We also discuss the limitations of, and potential for, contextual trajectories and moving area object trajectories. Our results show that PostGIS functions for moving point object trajectories are fast, reduce query complexity, and provide good indexing integration, especially concerning multi-dimensional indices; the results also reveal that trajectory data models outperform commonly used point-based data models.
Keywords: trajectories, moving objects, spatial databases, PostGIS, PostgreSQL