Generation of three-dimensional urban models
DOI:
https://doi.org/10.3989/ic.12.041Keywords:
3D Urban model, cityGML, LIDAR, automation, SDIAbstract
The use of 3D urban models extends increasingly to a broader range of areas and applications, but its use as a standard tool in the process of realization of the architectural and urban design is limited by the slow pace of the generation processes of models and the derived high cost of realization and maintenance of the models. That is why we find that its use, the size of the project permitting, often framed in purposes of visualization in the final stage. The authors of this paper have developed a methodology for the automation of the process of generation of these city models, cut time and costs, and that will allow a greater generalization of its use.
Downloads
References
(1) Martínez, E., Álvarez, M., Arquero, A., Romero, M. (2010). Apoyo a la selección de emplazamientos óptimos de edificios. Localización de un edificio universitario mediante el Proceso Analítico Jerárquico (AHP) Informes de la Construcción, 519(62): 35-45.
(2) Kada, M. (2009). The 3D Berlin Proyect. Fritsch, D. (ed.): Photogrammetric Week '09, Wichmann Verlag, Heidelberg.
(3) Brenner, C. (2001). City Models-Automation in research and practice. Fritsch/Spiller (eds.): Photogrammetric Week '01, Herbert Wichmann Verlag, Heidelberg.
(4) Brenner, C. (2000). Towards Fully Automatic Generation of City Models. IAPRS Vol. XXXIII, Part B3/1, Comm. III, ISPRS Congress, Amsterdam.
(5) Groot, R., McLaughlin, JD. (2000). Geospatial Data Infrastructure-Concepts, Cases, and Good Practice. Oxford University Press.
(6) Foley, J., van Dam, A., Feiner, S., Hughes, J. (1990). Computer Graphics: Principles and Practice, Second Edition, Addison-Wesley, Reading, Massachusetts.
(7) Finat, J., et al. (2010). Una aproximación semántica a sistemas de información 3D para la resolución de problemas de accesibilidad en patrimonio construido, ACE: Architecture, City and Environment, 13.
(8) Antoniou, G., Van Harmelen, F. (2004). A Semantic Web Primer. Massachusetts Institute of Technology, Londres.
(9) Hundler, J. (2001). Agents and semantic Web. IEEE Intelligent Systems, 16(2), Mar. /Apr. http://dx.doi.org/10.1109/5254.920597
(10) Booch, G., Rumbaugh, J., Jacobson, I. (1997). Unified Modeling Language User Guide. Addison-Wesley.
(11) Kolbe, TH., Grogër, G. (2003). Towards unified 3D city models, Schiewe, J., Hahn, M, Madden, M, Sester, M (eds): Challenges in Geospatial Analysis, Integration and Visualization, II. Proc. of Joint ISPRS Workshop, Stuttgart.,
(12) Kolbe, TH., Gröger, G. (2004). Unified Representation of 3D City Models. Geoinformation Science Journal, 4 (1).
(13) Ambercore LIDAR (2008). A White Paper of Lidar Mapping [En línea] Disponible en: http://www.ambercore.com/files/TerrapointWhitePaper.pdf.
(14) Díez, A., Arozarena, A., Orme-o, S., Aguirre, J., Rodríguez, R., Saenz, A. (2008). Integración y optimización de tecnologías y metodologías Lidar y fotogramétricas para la producción cartográfica. Proceedings of The international archives of the photogrammetry, remote sensing and spatial information sciences, ISPRS congress Beijing.
(15) Mather, P.M. (1985). A computationally-efficient maximum-likelihood classifier employing prior probabilities for remotely-sensed data. International Journal of Remote Sensing, 6. http://dx.doi.org/10.1080/01431168508948456
(16) Tso, B., Mather, P.M. (2001). Classification Methods for Remotely Sensed Data, Taylor &.Francis, Londres. http://dx.doi.org/10.4324/9780203303566
(17) Rodríguez, R., Álvarez, M., Miranda, M., Díaz, A., Papí, F. (2011). Automatic Generation of 3D Virtual Cities from Lidar Data and High Resolution Images. Proceedings of Ist Panel Symposium Emerged/Emerging "disruptive" Technologies, Madrid.
(18) Swain, P.H., Davis, S.M. (1978). Remote Sensing: The Quantitative Approach, McGraw-Hill, New York.
(19) Strahler, A.H. (1980). The use of prior probabilities in maximum likelihood classification of remotely sensed data. Remote Sensing of Environment, 10: 135-163. http://dx.doi.org/10.1016/0034-4257(80)90011-5
(20) Hutchinson, C.F. (1982). Techniques for combining Landsat and ancillary data for digital classification improvement. Photogrammetric Engineering and Remote Sensing, 48.
(21) Lee, D. T., Schachter, B. J. (1980). Two Algorithms for Constructing a Delaunay Triangulation. Int. J. Computer Information Sci, 9.
(22) Kada, M. (2007). 3D Building Generalisation by Roof Simplification and Typification. Proceedings of the 23th International Cartographic Conference, Moscu.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2013 Consejo Superior de Investigaciones Científicas (CSIC)

This work is licensed under a Creative Commons Attribution 4.0 International License.
© CSIC. Manuscripts published in both the print and online versions of this journal are the property of the Consejo Superior de Investigaciones Científicas, and quoting this source is a requirement for any partial or full reproduction.
All contents of this electronic edition, except where otherwise noted, are distributed under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence. You may read the basic information and the legal text of the licence. The indication of the CC BY 4.0 licence must be expressly stated in this way when necessary.
Self-archiving in repositories, personal webpages or similar, of any version other than the final version of the work produced by the publisher, is not allowed.







