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Articles

Integration of CityGML and Oracle Spatial for implementing 3D network analysis solutions and routing simulation within 3D-GIS environment

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Pages 221-237 | Received 22 Mar 2013, Accepted 23 Sep 2013, Published online: 19 Dec 2013

Figures & data

Figure 1. MUSCLE model process.

Figure 1. MUSCLE model process.

Figure 2. 3D model generation user interface.

Figure 2. 3D model generation user interface.

Figure 3. Generating corridors of a building from raster floor plans.

Figure 3. Generating corridors of a building from raster floor plans.

Figure 4. Generating rooms of a building from raster floor plans.

Figure 4. Generating rooms of a building from raster floor plans.

Figure 5. Generating the network model of a building from floor plans.

Figure 5. Generating the network model of a building from floor plans.

Figure 6. The five LOD defined by CityGML (Citation12).

Figure 6. The five LOD defined by CityGML (Citation12).

Figure 7. TransportationComplex in LOD 0, 1, and 2–4 (example shows part of a motorway) (Citation12).

Figure 7. TransportationComplex in LOD 0, 1, and 2–4 (example shows part of a motorway) (Citation12).

Figure 8. Data generation process of a building’s network model in LOD0 using 3D model generation software.

Figure 8. Data generation process of a building’s network model in LOD0 using 3D model generation software.

Table 1. A 3D network model in City GML, which uses a Transportation Module.

Figure 9. Viewing modes of 3D spatial objects in our proposed 3D-GIS implementation.

Figure 9. Viewing modes of 3D spatial objects in our proposed 3D-GIS implementation.

Figure 10. Building model (Textured viewing mode).

Figure 10. Building model (Textured viewing mode).

Figure 11. Network model.

Figure 11. Network model.

Figure 12. Oracle network data model.

Figure 12. Oracle network data model.

Figure 13. Main network tables.

Figure 13. Main network tables.

Table 2. Columns of node table in the network model.

Table 3. Columns of link table in the network model.

Table 4. A metadata table called USER_SDO_NETWORK_METADATA.

Figure 14. Automatic network creation tool.

Figure 14. Automatic network creation tool.

Figure 15. 3D network analysis tool.

Figure 15. 3D network analysis tool.

Figure 16. Shortest path between two nodes without any constraint.

Figure 16. Shortest path between two nodes without any constraint.

Figure 17. Recalculated shortest path considering avoided elevators in a part of building.

Figure 17. Recalculated shortest path considering avoided elevators in a part of building.

Figure 18. All nodes within a 40-m walking distance to node 3354.

Figure 18. All nodes within a 40-m walking distance to node 3354.

Figure 19. All nodes within a 40-m walking distance to node 3354 after constraints applied.

Figure 19. All nodes within a 40-m walking distance to node 3354 after constraints applied.

Figure 20. All paths to the 10 nearest neighbors of node 3354.

Figure 20. All paths to the 10 nearest neighbors of node 3354.

Table 5. 10 nearest neighbors of node 3354.

Figure 21. All three best solutions between nodes 3354 and 3655.

Figure 21. All three best solutions between nodes 3354 and 3655.

Figure 22. A sample TSP analysis.

Figure 22. A sample TSP analysis.

Table 6. Details of TSP analysis.

Figure 23. Routing simulation process of the instruction engine (The red point (■) is the user).

Figure 23. Routing simulation process of the instruction engine (The red point (■) is the user).

Figure 24. Generating instructions based on side direction calculation for routing.

Figure 24. Generating instructions based on side direction calculation for routing.

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