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GI_FORUM - Journal for Geographic Information Science
Article . 2018 . Peer-reviewed
Data sources: Crossref
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Evaluating Spatio-temporal Data Models for Trajectories in PostGIS Databases

Authors: Anita Graser;

Evaluating Spatio-temporal Data Models for Trajectories in PostGIS Databases

Abstract

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.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Average
gold