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Spatio-temporal access methods: a survey (2010 - 2017)

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Abstract

The volume of spatio-temporal data is growing at a rapid pace due to advances in location-aware devices, e.g., smartphones, and the popularity of location-based services, e.g., navigation services. A number of spatio-temporal access methods have been proposed to support efficient processing of queries over the spatio-temporal data. Spatio-temporal access methods can be classified according to the type of data being indexed into the following categories: (1) indexes for historical spatio-temporal data, (2) indexes for current and recent spatio-temporal data, (3) indexes for future spatio-temporal data, (4) indexes for past, present, and future spatio-temporal data, (5) indexes for spatio-temporal data with associated textual data, and (6) parallel and distributed spatio-temporal systems and indexes. This survey is Part 3 of our previous surveys on the same subject (Mokbel et al. IEEE Data Eng Bull 26(2):40–49, 2003; Nguyen-Dinh et al. IEEE Data Eng Bull 33(2):46–55, 2010). In this survey, we present an overview and a broad classification of the spatio-temporal access methods published between 2010 and 2017.

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Acknowledgements

This work has been partially supported by the National Science Foundation under Grant Number III-1815796.

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  1. Purdue University, West Lafayette, IN, USA

    Ahmed R. Mahmood, Sri Punni & Walid G. Aref

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  1. Ahmed R. Mahmood
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Mahmood, A.R., Punni, S. & Aref, W.G. Spatio-temporal access methods: a survey (2010 - 2017). Geoinformatica 23, 1–36 (2019). https://doi.org/10.1007/s10707-018-0329-2

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