3D city models

3D city models are digital models of urban areas that represent terrain surfaces, sites, buildings, vegetation, infrastructure and landscape elements as well as related objects (e.g., city furniture) belonging to urban areas. Their components are described and represented by corresponding two-dimensional and three-dimensional spatial data and geo-referenced data. 3D city models support presentation, exploration, analysis, and management tasks in a large number of different application domains. In particular, 3D city models allow "for visually integrating heterogeneous geoinformation within a single framework and, therefore, create and manage complex urban information spaces." [1][2]

Storage of 3D City Models

To store 3D city models, both file-based and database approaches are used. There is no single, unique representation schema due to the heterogeneity and diversity of 3d city model contents.

Encoding of Components

Components of 3D city models are encoded by common file and exchange formats for 2D raster-based GIS data (e.g., GeoTIFF), 2D vector-based GIS data (e.g., AutoCAD DXF), 3D models (e.g., .3DS, .OBJ), and 3D scenes (e.g., Collada, Keyhole Markup Language) such as supported by CAD, GIS, and computer graphics tools and systems. All components of a 3D city model have to be transformed into a common geographic coordinate system.

Databases

A database for 3D city models stores its components in a hierarchically structured, multi-scale way, which allows for a stable and reliable data management and facilitates complex GIS modeling and analysis tasks. For example, the 3D City Database is a free 3D geo database to store, represent, and manage virtual 3D city models on top of a standard spatial relational database.[3] A database is required if 3D city models have to be continuously managed. 3D city model databases form a key element in 3D spatial data infrastructures that require support for storing, managing, maintenance, and distribution of 3D city model contents.[4] Their implementation requires support of a multitude of formats (e.g., based on FME multi formats). As common application, geodata download portals can be set up for 3D city model contents (e.g., virtualcityWarehouse).[5]

CityGML

The Open Geospatial Consortium (OGC) defines an explicit XML-based exchange format for 3D city models, CityGML, which supports not only geometric descriptions of 3D city model components but also the specification of semantics and topology information.[6]

Construction of 3D City Models

Level of Detail

3D city models are typically constructed at various levels of detail (LOD) to provide notions of multiple resolutions and at different levels of abstraction. Other metrics such as the level of spatio-semantic coherence and resolution of the texture can be considered a part of the LOD.[7] For example, CityGML defines five LODs for building models:

There exist also approaches to generalize a given detailed 3D city model by means of automated generalization.[8] For example, a hierarchical road network (e.g., OpenStreetMap) can be used to group 3D city model components into "cells"; each cell is abstracted by aggregating and merging contained components.

GIS Data

GIS data provide the base information to build a 3D city model such as by digital terrain models, road networks, land use maps, and related geo-referenced data. GIS data also includes cadastral data that can be converted into simple 3D models as, for example, in the case of extruded building footprints. Core components of 3D city models form digital terrain models (DTM) represented, for example, by TINs or grids.

CAD Data

Typical sources of data for 3D city model also include CAD models of buildings, sites, and infrastructure elements. They provide a high level of detail, possible not required by 3D city model applications, but can be incorporated either by exporting their geometry or as encapsulated objects.

BIM Data

Building information models represent another category of geo-spatial data that can be integrated into a 3D city model providing the highest level of detail for building components.

Integration at Visualization Level

Complex 3D city models typically are based on different sources of geodata such as geodata from GIS, building and site models from CAD and BIM. It is one of their core properties to establish a common reference frame for heterogeneous geo-spatial and geo-referenced data, i.e., the data need not to be merged or fusioned based on one common data model or schema. The integration is possible by sharing a common geo-coordinate system at the visualization level.[9]

Building Reconstruction

The simplest form of building model construction consist in extruding the footprint polygons of buildings, e.g., taken from the cadaster, by pre-compute average heights. In practice, 3D models of buildings of urban regions are generated based on capturing and analyzing 3D point clouds (e.g., sampled by terrestrial or aerial laser scanning) or by photogrammetric approaches. To achieve a high percentage of geometrically and topologically correct 3D building models, digital terrain surfaces and 2D footprint polygons are required by automated building reconstruction tools such as BREC.[10] One key challenge is to find building parts with their corresponding roof geometry. "Since fully automatic image understanding is very hard to solve, semi-automatic components are usually required to at least support the recognition of very complex buildings by a human operator."[11] Statistical approaches are common for roof reconstruction based on airborne laser scanning point clouds. [12][13]

Fully automated processes exist to generate LOD1 and LOD2 building models for large regions. For example, the Bavarian Office for Surveying and Spatial Information is responsible for about 8 million building models at LOD1 and LOD2.[14]

Visualization of 3D City Models

The visualization of 3D city models represents a core functionality required for interactive applications and systems based on 3D city models.

Real-Time Rendering of 3D City Models

Providing high quality visualization of massive 3D city models in a scalable, fast, and cost efficient manner is still a challenging task due to the complexity in terms of 3D geometry and textures of 3D city models. Real-time rendering provides a large number of specialized 3D rendering techniques for 3D city models. Examples of specialized real-time 3D rendering include:

Real-time rendering algorithms and data structures are listed by the virtual terrain project.[22]

Service-Based Rendering of 3D City Models

Service-oriented architectures (SOA) for visualizing 3D city models offer a separation of concerns into management and rendering and their interactive provision by client applications. For SOA-based approaches, 3D portrayal services[23] are required, whose main functionality represents the portrayal in the sense of 3D rendering and visualization.[24] SOA-based approaches can be distinguished into two main categories, currently discussed in the Open Geospatial Consortium:

Map-Based Visualization

A map-based technique, the "smart map" approach, aims at providing "massive, virtual 3D city models on different platforms namely web browsers, smartphones or tablets, by means of an interactive map assembled from artificial oblique image tiles." [26] The map tiles are synthesized by an automatic 3D rendering process of the 3D city model; the map tiles, generated for different levels-of-detail, are stored on the server. This way, the 3D rendering is completely performed on the server's side, simplifying access and usage of 3D city models. The 3D rendering process can apply advanced rendering techniques (e.g., global illumination and shadow calculation, illustrative rendering), but does not require client devices to have advanced 3D graphics hardware. Most importantly, the map-based approach allows for distributing and using complex 3D city models with having to stream the underlying data to client devices - only the pre-generated map tiles are sent. This way, "(a) The complexity of the 3D city model data is decoupled from data transfer complexity (b) the implementation of client applications is simplified significantly as 3D rendering is encapsulated on server side (c) 3D city models can be easily deployed for and used by a large number of concurrent users, leading to a high degree of scalability of the overall approach." [27]

Applications

3D city models as multi-purpose models of spatial environments are used in a growing number of different application domains. Examples:

References

  1. ↑ "J. Döllner, K. Baumann, H. Buchholz: Virtual 3D City Models as Foundation of Complex Urban Information Spaces. 11th international conference on Urban Planning and Spatial Development in the Information Society (REAL CORP), (Manfred Schrenk, ed.), CORP – Competence Center of Urban and Regional Planning, pp. 107–112, 2006.".
  2. ↑ "Example video for 3D city models as complex information spaces".
  3. ↑ "3D City DB Web Site www.3dcitydb.org".
  4. ↑ "virtual city database for 3D city and landscape models".
  5. ↑ "virtualcityWarehouse".
  6. ↑ T. H. Kolbe: Representing and Exchanging 3D City Models with CityGML. 3D Geo-Information Sciences, J. Lee, S. Zlatanova,W. Cartwright, G. Gartner, L. Meng, and M. P. Peterson, Eds. Springer Berlin Heidelberg, 2009, pp. 15–31
  7. ↑ Biljecki, F.; Ledoux, H.; Stoter, J.; Zhao, J. (2014). "Formalisation of the level of detail in 3D city modelling". Computers, Environment and Urban Systems 48 (1): 1–15. doi:10.1016/j.compenvurbsys.2014.05.004.
  8. ↑ T. Glander, J. Döllner: Techniques for Generalizing Building Geometry of Complex Virtual 3D City Models. Advances in 3D Geoinformation Systems, (Peter van Oosterom and Sisi Zlatanova and Friso Penninga and Elfriede M. Fendel, ed.), Lecture Notes in Geoinformation and Cartography, Springer, pp. 381–400, 2008.
  9. ↑ J. Döllner, B. Hagedorn: Integrating Urban GIS, CAD, and BIM Data By Service-Based Virtual 3D City-Models. Urban and Regional Data Management: UDMS 2007 Annual, (Massimo Rumor and Volker Coors and Elfriede M. Fendel and Sisi Zlatanova, ed.), Taylor & Francis Ltd, Stuttgart, Germany, pp. 157–170, 2007.
  10. ↑ http://www.virtualcitysystems.de/en/products/buildingreconstruction
  11. ↑ N. Haala, M. Kada: An update on automatic 3D building reconstruction. ISPRS Journal of Photogrammetry and Remote Sensing 65 (2010), 570–580.
  12. ↑ H. Huang, C. Brenner, M. Sester: 3D building roof reconstruction from point clouds via generative models. GIS 2011: 16-24.
  13. ↑ "K. Hammoudi: Contributions to the 3D city modeling: 3D polyhedral building model reconstruction from aerial images and 3D facade modeling from terrestrial 3D point cloud and images. Ph.D. thesis in signal and image processing, Université Paris-Est, 234p., 2011.".
  14. ↑ "Bavarian LOD2 Building Model Project".
  15. ↑ M. Vaaraniemi, M. Treib, R. Westermann: High-Quality Cartographic Roads on High-Resolution DEMs. Journal of WSCG 19(2):41-48, 2011.
  16. ↑ A. Semmo et al.: Real-Time Rendering of Water Surfaces with Cartography-Oriented Design. Proceedings International Symposium on Computational Aesthetics in Graphics, Visualization, and Imaging (CAe), pp. 5–14, 2013.
  17. ↑ D. Limberger et al.: Single-Pass Rendering of Day and Night Sky Phenomena. Proceedings of the Vision, Modeling, and Visualization Workshop 2012, Eurographics Association, pp. 55-62, 2012.
  18. ↑ F. Losasso, H. Hoppe: Geometry clipmaps: Terrain rendering using nested regular grids. ACM Trans. Graphics (SIGGRAPH), 23(3), 2004.
  19. ↑ http://www.youtube.com/watch?v=tU5d6WuSglk
  20. ↑ http://www.youtube.com/watch?v=bT01QsZMYDE
  21. ↑ http://www.hpi.uni-potsdam.de/doellner/publications/year/2014/2390/PSTD2014.html Multiperspective Views for 3D City Models
  22. ↑ http://vterrain.org/LOD/Papers/
  23. ↑ http://www.opengeospatial.org/projects/initiatives/3dpie
  24. ↑ J. Klimke, J. Döllner: Service-oriented Visualization of Virtual 3D City Models. Directions Magazine, 2012. http://www.directionsmag.com/articles/service-oriented-visualization-of-virtual-3d-city-models/226560
  25. ↑ J. Döllner, B. Hagedorn: Server-Based Rendering of Large 3D Scenes for Mobile Devices Using G-Buffer Cube Maps. Web3D '12 Proceedings of the 17th International Conference on 3D Web Technology, pp. 97-100, 2012.
  26. ↑ J. Klimke et al.: "Scalable Multi-Platform Distribution of Spatial 3D Contents". ISPRS 8th 3D GeoInfo Conference & WG II/2 Workshop 27–29 November 2013, Istanbul, Turkey, (U. Isikdag, ed.), vol. II-2/W1, ISPRS Annals, ISPRS, pp. 193-200, 2013.
  27. ↑ J. Klimke et al.: "Scalable Multi-Platform Distribution of Spatial 3D Contents". ISPRS 8th 3D GeoInfo Conference & WG II/2 Workshop 27–29 November 2013, Istanbul, Turkey, (U. Isikdag, ed.), vol. II-2/W1, ISPRS Annals, ISPRS, pp. 193-200, 2013.
  28. ↑ M. Vaaraniemi et al.: Intelligent Prioritization and Filtering of Labels in Navigation Maps. Journal of WSCG, 2014.
  29. ↑ "E. Ben-Joseph et al.: Urban simulation and the luminous planning table: Bridging the gap between the digital and the tangible. Journal of Planning Education and Research 21 (2), 196-203, 2001.".
  30. ↑ http://www.gsdi.org/gsdiconf/gsdi12/slides/2.4a.pdf
  31. ↑ http://virtualcitysystems.de/images/pdf/3d-gdi/EN_3D_SDI_2013_Flyer.pdf
  32. ↑ http://virtualcitysystems.de/en/references.html#research DETORBA
  33. ↑ C. Carneiro et al.: Solar radiation over the urban texture: LiDAR data and image processing techniques for environmental analysis at city scale. 3D Geo-Information Sciences, 319-340, 2008.
  34. ↑ J. Engel, J. Döllner: Approaches Towards Visual 3D Analysis for Digital Landscapes and Its Applications. Digital Landscape Architecture Proceedings 2009, pp. 33-41, 2009.
  35. ↑ "M. Lancelle and D. Fellner, "Current Issues on 3D City Models," Proc. Image and Vision Computing, 2004, pp. 363–369".
  36. ↑ "D. Iwaszczuk et al.: Matching of 3D building models with IR images for texture extraction. JURSE 2011 - Joint Urban Remote Sensing Event, 25-28".
  37. ↑ L. Hoegner et al.: Automatic extraction of textures from infrared image sequences and database integration for 3D building models. PFG Photogrammetrie Fernerkundung Geoinformation, 2007(6): 459-468, 2007.
  38. ↑ M. Trapp et al.: Colonia 3D - Communication of Virtual 3D Reconstructions in Public Spaces. International Journal of Heritage in the Digital Era (IJHDE), vol. 1, no. 1, pp. 45-74, 2012.
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  40. ↑ "IEEE Intelligent Transportation Systems Society".
  41. ↑ "C. Portalés et al.: Augmented reality and photogrammetry: A synergy to visualize physical and virtual city environments. ISPRS J. Photogramm. Remote Sensing, 65, 134-142, 2010.".

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