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Using GIS Data to Build Informed Virtual Geographic Environments (IVGE)

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DOI: 10.4236/jgis.2013.56052    4,680 Downloads   6,759 Views   Citations
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ABSTRACT

In this paper, we propose a novel approach to automatically building Informed Virtual Geographic Environments (IVGE) using data provided by Geographic Information Systems (GIS). The obtained IVGE provides 2D and 3D geographic information for visualization and simulation purposes. Conventional VGE approaches are generally built upon a grid-based representation, raising the well-known problems of the lack of accuracy of the localized data and the difficulty to merge data with multiple semantics. On the contrary, our approach uses a topological model and provides an exact representation of GIS data, allowing an accurate geometrical exploitation. Moreover, our model can merge semantic information, even if spatially overlapping. In addition, the proposed IVGE contains spatial information which can be enhanced thanks to a geometric abstraction method. We illustrate this model with an application which automatically extracts the required data from standard GIS files and allows a user to navigate and retrieve information from the computed IVGE.

 

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

M. Mekni, "Using GIS Data to Build Informed Virtual Geographic Environments (IVGE)," Journal of Geographic Information System, Vol. 5 No. 6, 2013, pp. 548-558. doi: 10.4236/jgis.2013.56052.

References

[1] R. Andersen, J. L. Berrou and A. Gerodimos, “On Some Limitations of Grid-Based (CA) Pedestrian Simulation Models,” In VRlab, EPFL, 2005.
[2] M. Kallmann, H. Bieri and D. Thalmann, “Fully Dynamic Constrained Delaunay Triangulations,” Geometric Modelling for Scientific Visualization, 2003.
[3] F. Lamarche and S. Donikian, “Crowds of Virtual Humans: A New Approach for Real Time Navigation in Complex and Structured Environments,” Computer Graphics Forum, Eurographics’04, 2004.
[4] J. Gong and L. Hui, “Virtual Geographical Environments: Concept, Design, and Applications,” 1999.
[5] D. Demyen and M. Buro, “Efficient Triangulation-Based Pathfinding,” 2006.
[6] M. F. Goodchild, “GIS and Disasters: Planning for Catastrophe,” Computers, Environment and Urban Systems, Vol. 30, No. 3, 2006, pp. 227-229.
http://dx.doi.org/10.1016/j.compenvurbsys.2005.10.004
[7] N. Chrisman, “Exploring Geographical Information Systems,” 2nd Edition, John Wiley and Sons Inc., 2001.
[8] D. Arctur and M. Zeiler, “Designing Geodatabases: Case Studies in GIS Data Modeling,” ESRI Press, 2004.
[9] P. Longley, M. Goodchild, M. David and D. Rhind, “Geographic Information Systems and Science,” Wiley and Son. Inc., ESRI Press, 2002.
[10] S. Fortheringham and P. Rogerson, “Spatial Anaysis and GIS’s,” Taylor & Francis, LTD, 2002.
[11] L. Zhou, G. Lu, Y. Sheng, H. Xu and H. Wang, “A 3D GIS Spatial Data Model Based On Cell Complex,” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 37, 2008, pp. 905-908.
[12] M. Mekni, N. Sahli, B. Moulin and H. Haddad, “Using Multi-Agent Geo-Simulation Techniques for the Detection of Risky Areas for Trains,” Simulation, Vol. 86, No. 12, 2010, pp. 763-775.
http://dx.doi.org/10.1177/0037549709359354
[13] J. Zhu, J. Gong, H. Lin, W. Li, J. Zhang and X. Wu, “Spatial Analysis Services in Virtual Geographic Environment Based on Grid Technologies,” MIPPR 2005: Geospatial Information, Data Mining, and Applications, Vol. 6045, No. 1, 2005, pp. 604-615.
[14] M. Mekni and B. Moulin, “Holonic Modelling of Large Scale Geographic Environments,” 2007.
[15] F. Tecchia, C. Loscos and Y. Chrysanthou, “Visualizing Crowds in Real-Time,” Computer Graphics Forum, Vol. 21, No. 4, 2002, pp. 753-765.
http://dx.doi.org/10.1111/1467-8659.00633
[16] M. Mekni, “Crowd Simulation Using Informed Virtual Geographic Environments (IVGE),” 2012.
[17] A. Botea, M. Muller and J. Schaeffer, “Near Optimal Hierarchical Path-Finding,” Journal of Game Development, Vol. 1, 2004, pp. 7-28.
[18] L. G. Da and S. R. Musse, “Real-Time Generation of Populated Virtual Cities,” 2006.
[19] W. Shao and D. Terzopoulos, “Environmental Modeling for Autonomous Virtual Pedestrians,” Digital Human Modeling for Design and Engineering Symposium, 2005.
[20] S. Paris, S. Donikian and N. Bonvalet, “Environmental Abstraction and Path Planning Techniques for Realistic Crowd Simulation,” Computer Animation and Virtual Worlds, Vol. 17, No. 3-4, 2006, pp. 325-335.
http://dx.doi.org/10.1002/cav.136
[21] D. Brown, “Agent-Based Models,” The Earths Changing Land: An Encyclopaedia of Land-Use and Land-Cover Change, Greenwood Publishing Group, Westport, 2006, pp. 7-13.
[22] M. Mekni, “Abstraction of Informed Virtual Geographic Environments,” Geo-Spatial Information Science, Vol. 15, No. 1, 2012, pp. 27-36.
http://dx.doi.org/10.1080/10095020.2012.708150
[23] S.-G. Chen and J.-Y. Wu, “A Geometric Interpretation of Weighted Normal Vectors and Its Improvements,” 2005.
[24] GDAL: Geospatial Data Abstraction Library.

  
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