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Original Articles

Spatiotemporal data model for network time geographic analysis in the era of big data

, , , , &
Pages 1041-1071 | Received 29 Jun 2015, Accepted 02 Oct 2015, Published online: 05 Nov 2015

Figures & data

Figure 1. Space-time paths in planar space.

Figure 1. Space-time paths in planar space.

Figure 2. A space-time prism in planar space.

Figure 2. A space-time prism in planar space.

Figure 3. A space-time lifeline in planar space.

Figure 3. A space-time lifeline in planar space.

Figure 4. Space-time intersections.

Figure 4. Space-time intersections.

Figure 5. Space-time path bundling.

Figure 5. Space-time path bundling.

Figure 6. A network space-time path in (x, y, t) space.

Figure 6. A network space-time path in (x, y, t) space.

Figure 7. A network space-time path in CLR space.

Figure 7. A network space-time path in CLR space.

Figure 8. A network space-time prism in (x, y, t) space.

Figure 8. A network space-time prism in (x, y, t) space.

Figure 9. A network space-time prism in CLR space.

Figure 9. A network space-time prism in CLR space.

Figure 10. A network space-time lifeline in CLR space.

Figure 10. A network space-time lifeline in CLR space.

Table 1. Space-time intersections of network time geographic entities in the CLR space.

Figure 11. Paths bundling in CLR space.

Figure 11. Paths bundling in CLR space.

Figure 12. Spatiotemporal data model for network time geographic entities in CLR space.

Figure 12. Spatiotemporal data model for network time geographic entities in CLR space.

Figure 13. Shenzhen road network.

Figure 13. Shenzhen road network.

Figure 14. Storage space of space-time paths.

Figure 14. Storage space of space-time paths.

Figure 15. Storage space of space-time prisms.

Figure 15. Storage space of space-time prisms.

Figure 16. The path-path intersection query performance.

Figure 16. The path-path intersection query performance.

Figure 17. The window-path intersection query performance: (a) under different window sizes; (b) under different time intervals.

Figure 17. The window-path intersection query performance: (a) under different window sizes; (b) under different time intervals.

Figure 18. Computational performance of the station-prism within query and the prism-prism intersection query.

Figure 18. Computational performance of the station-prism within query and the prism-prism intersection query.

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