Generating Orthorectified MultiPerspective 2.5D Maps to Facilitate Web GISBased Visualization and Exploitation of Massive 3D City Models
Abstract
:1. Introduction
 Support for various 3D model formats. 3D models come in a wide variety of formats, including .3ds, .obj and .dae.
 Support for LOD structure and spatial partitioning. Given limited computational power, a welldesigned spatialpartitioning and outofcore rendering scheme must be employed to generate 2.5D maps at a sufficiently high spatial resolution. By leveraging an LOD structure, a large 3D city model can be rendered into a grid of map tiles, but these map tiles need be accurately georeferenced so they can be stitched back together to form a seamless 2.5D mosaic.
 Support for custom map perspectives. An oblique perspective is defined by a camera’s azimuth and elevation angle. A multiperspective set of 2.5D maps can potentially afford a complete view of a 3D city model.
 Support for orthorectification. The presence of terrain and the use of an oblique perspective may subject a set of 2.5D maps to distortion and misalignment. Orthorectification brings a multiperspective set of 2.5D maps back into a common reference system.
2. Methods
2.1. Constructing an Integrated Oblique Image Renderer
2.2. Automating GCP Coordinates Retrieval for Orthorectification
 Locate the row and column number of the map tile that contains the GCP by the orthographic coordinates of this GCP.
 Create an OpenGL point primitive using the GCP coordinates and then render the point together with the 3D city model using the associated orthographic camera. In the GPU shading pipeline, the GCP primitive is shaded in red and the 3D city model in pure black with all textures and materials disabled (Figure 7B). In Figure 6B, the background pixels associated with the 3D city model are not discarded to show how the GCPs are displaced in an oblique view against the orthographic view.
 Traverse the pixels in the RTT after the render loop is completed. The red pixels are retained (Figure 7C) while black ones are discarded. The center of the cluster of red pixels is assumed to be the coordinates of this GCP in the oblique space.
3. Application
3.1. Generating 2.5D Maps from 3D City Models
3.2. Comparison of 2.5D and 3D Representations in WebBased Visualization of 3D City Models
3.3. Geometric Measurement on 2.5D Maps and Accuracy Assessment
3.4. Workflow for Integrating 2.5D Maps into Web GIS
3.5. Integrating Orthorectified 2.5D Images into a Street Map for Campus Navigation
3.6. The Fusion of Scientific Data and Art in 2.5D Cartography
4. Conclusions
 Interactive analysis. Geometric measurement is typical of interactive analysis in 3D city models. We have shown by example that the geometric measurement of buildings can be effectively conducted on 2.5D maps. The accuracy assessment revealed that measurement of building height on 2.5D maps is subject to minor errors. Although the RMSD is as small as 0.701 m, it must be considered in engineering activities such as cadastral survey. The uncertainty in geometric measurement on 2.5D maps may be related to the inaccurate positioning of a point, inaccurate alignment of lines, or insufficient map resolution.
 Interactive visualization. We conclude that 2.5D maps are a compact data representation optimized for web data streaming and mapping. Our case study showed that a compression ratio of 51:1 was achievable by transforming an OAP3D of 81.5 GB into an eightperspective set of 2.5D maps of 1.6 GB. Efficient streaming of highresolution 2.5D maps to a client can ensure a highquality visualization experience.
Acknowledgments
Author Contributions
Conflicts of Interest
References
 Bruse, M.; Fleer, H. Simulating surface–plant–air interactions inside urban environments with a three dimensional numerical model. Environ. Model. Softw. 1998, 13, 373–384. [Google Scholar] [CrossRef]
 Huang, B.; Jiang, B.; Li, H. An integration of GIS, virtual reality and the Internet for visualization, analysis and exploration of spatial data. Int. J. Geogr. Inf. Sci. 2001, 15, 439–456. [Google Scholar] [CrossRef]
 Lin, H.; Chen, M.; Lu, G. Virtual geographic environment: A workspace for computeraided geographic experiments. Ann. Assoc. Am. Geogr. 2013, 103, 465–482. [Google Scholar] [CrossRef]
 Li, W.; Gong, J.; Yu, P.; Duan, Q.; Zou, Y. A streambased Parasitic Model for implementing Mobile Digital Earth. Int. J. Dig. Earth 2014, 7, 38–52. [Google Scholar] [CrossRef]
 Ledoux, H.; Meijers, M. Topologically consistent 3D city models obtained by extrusion. Int. J. Geogr. Inf. Sci. 2011, 25, 557–574. [Google Scholar] [CrossRef]
 Cheng, L.; Gong, J.; Li, M.; Liu, Y. 3D building model reconstruction from multiview aerial imagery and lidar data. Photogramm. Eng. Remote Sens. 2011, 77, 125–139. [Google Scholar] [CrossRef]
 Remondino, F.; Barazzetti, L.; Nex, F.; Scaioni, M.; Sarazzi, D. UAV photogrammetry for mapping and 3d modeling–current status and future perspectives. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2011, 38, 22–37. [Google Scholar] [CrossRef]
 Liang, J.; Shen, S.; Gong, J.; Liu, J.; Zhang, J. Embedding usergenerated content into oblique airborne photogrammetrybased 3D city model. Int. J. Geogr. Inf. Sci. 2016. [Google Scholar] [CrossRef]
 Ranzinger, M.; Gleixner, G. GIS datasets for 3D urban planning. Comput. Environ. Urban Syst. 1997, 21, 159–173. [Google Scholar] [CrossRef]
 Zhang, X.; Zhu, Q.; Wang, J. 3D city models based spatial analysis to urban design. Geogr. Inf. Sci. 2004, 10, 82–86. [Google Scholar] [CrossRef]
 Biljecki, F.; Stoter, J.; Ledoux, H.; Zlatanova, S.; Çöltekin, A. Applications of 3D city models: State of the art review. ISPRS Int. J. GeoInf. 2015, 4, 2842–2889. [Google Scholar] [CrossRef]
 Biljecki, F.; Heuvelink, G.B.; Ledoux, H.; Stoter, J. Propagation of positional error in 3D GIS: Estimation of the solar irradiation of building roofs. Int. J. Geogr. Inf. Sci. 2015, 29, 2269–2294. [Google Scholar] [CrossRef]
 Liang, J.; Gong, J.; Li, W.; Ibrahim, A.N. A visualizationoriented 3D method for efficient computation of urban solar radiation based on 3D–2D surface mapping. Int. J. Geogr. Inf. Sci. 2014, 28, 780–798. [Google Scholar] [CrossRef]
 Liang, J.; Gong, J.; Zhou, J.; Ibrahim, A.N.; Li, M. An opensource 3D solar radiation model integrated with a 3D Geographic Information System. Environ. Model. Softw. 2015, 64, 94–101. [Google Scholar] [CrossRef]
 Lukač, N.; Žalik, B. GPUbased roofs’ solar potential estimation using LiDAR data. Comput. Geosci. 2013, 52, 34–41. [Google Scholar] [CrossRef]
 Carrión, D.; Lorenz, A.; Kolbe, T.H. Estimation of the energetic rehabilitation state of buildings for the city of Berlin using a 3D city model represented in CityGML. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2010, 38, 31–35. [Google Scholar]
 Saran, S.; Wate, P.; Srivastav, S.K.; Krishna Murthy, Y.V.N. CityGML at semantic level for urban energy conservation strategies. Ann. GIS. 2015, 21, 27–41. [Google Scholar] [CrossRef]
 Boeters, R.; Arroyo Ohori, K.; Biljecki, F.; Zlatanova, S. Automatically enhancing CityGML LOD2 models with a corresponding indoor geometry. Int. J. Geogr. Inf. Sci. 2015, 29, 2248–2268. [Google Scholar] [CrossRef]
 Shiravi, S.; Zhong, M.; Beykaei, S.A.; Hunt, J.D.; Abraham, J.E. An assessment of the utility of LiDAR data in extracting baseyear floorspace and a comparison with the censusbased approach. Environ. Plan. B Plan. Des. 2015, 42, 708–729. [Google Scholar]
 Henn, A.; Römer, C.; Gröger, G.; Plümer, L. Automatic classification of building types in 3D city models. GeoInformatica 2012, 16, 281–306. [Google Scholar] [CrossRef]
 Royan, J.; Gioia, P.; Cavagna, R.; Bouville, C. Networkbased visualization of 3d landscapes and city models. IEEE Comput. Graph. Appl. 2007, 27, 70–79. [Google Scholar] [CrossRef] [PubMed]
 Yang, P.P.J.; Putra, S.Y.; Li, W. Viewsphere: A GISbased 3D visibility analysis for urban design evaluation. Environ. Plan. B Plan. Des. 2007, 34, 971–992. [Google Scholar] [CrossRef]
 Hofierka, J.; Zlocha, M. A new 3D solar radiation model for 3D city models. Trans. GIS. 2012, 16, 681–690. [Google Scholar] [CrossRef]
 Guo, R.; Li, L.; Ying, S.; Luo, P.; He, B.; Jiang, R. Developing a 3D cadastre for the administration of urban land use: A case study of Shenzhen, China. Comput. Environ. Urban Syst. 2013, 40, 46–55. [Google Scholar] [CrossRef]
 Duan, Q.; Gong, J.; Li, W.; Shen, S.; Li, R. Improved Cubemap model for 3D navigation in geovirtual reality. Int. J. Dig. Earth. 2015, 8, 877–900. [Google Scholar] [CrossRef]
 Wu, H.; He, Z.; Gong, J. A virtual globebased 3D visualization and interactive framework for public participation in urban planning processes. Comput. Environ. Urban Syst. 2010, 34, 291–298. [Google Scholar] [CrossRef]
 Hijazi, I.H.; Ehlers, M.; Zlatanova, S. NIBU: A new approach to representing and analysing interior utility networks within 3D geoinformation systems. Int. J. Dig. Earth. 2012, 5, 22–42. [Google Scholar] [CrossRef]
 Kwan, M.P.; Lee, J. Emergency response after 9/11: The potential of realtime 3D GIS for quick emergency response in microspatial environments. Comput. Environ. Urban Syst. 2005, 29, 93–113. [Google Scholar] [CrossRef]
 Lu, Z.; Im, J.; Quackenbush, L. A volumetric approach to population estimation using LiDAR remote sensing. Photogramm. Eng. Remote Sens. 2011, 77, 1145–1156. [Google Scholar] [CrossRef]
 Hildebrandt, D.; Timm, R. An assisting, constrained 3D navigation technique for multiscale virtual 3D city models. GeoInformatica 2014, 18, 537–567. [Google Scholar] [CrossRef]
 Amirebrahimi, S.; Rajabifard, A.; Mendis, P.; Ngo, T. A framework for a microscale flood damage assessment and visualization for a building using BIM–GIS integration. Int. J. Dig. Earth. 2016, 9, 363–386. [Google Scholar] [CrossRef]
 Liu, J.; Gong, J.H.; Liang, J.M.; Li, Y.; Kang, L.C.; Song, L.L.; Shi, S.X. A quantitative method for storm surge vulnerability assessment—A case study of Weihai City. Int. J. Dig. Earth 2016. [Google Scholar] [CrossRef]
 Qin, R. Change detection on LOD 2 building models with very high resolution spaceborne stereo imagery. ISPRS J. Photogramm. Remote Sens. 2014, 96, 179–192. [Google Scholar] [CrossRef]
 Shirley, P.; Ashikhmin, M.; Marschner, S. Fundamentals of Computer Graphics; CRC Press: Boca Raton, FL, USA, 2009. [Google Scholar]
 Krygier, J.B. Cartography as an art and a science? Cartogr. J. 1995, 32, 3–10. [Google Scholar] [CrossRef]
 Peuquet, D.J. An examination of techniques for reformatting digital cartographic data/Part 1: The rastertovector process. Cartogr. Int. J. Geogr. Inf. Geovis. 1981, 18, 34–48. [Google Scholar]
 Peuquet, D.J. An examination of techniques for reformatting digital cartographic data/Part 2: The vectortoraster process. Cartogr. Int. J. Geogr. Inf. Geovis. 1981, 18, 21–33. [Google Scholar]
 Berry, J.K. Fundamental operations in computerassisted map analysis. Int. J. Geogr. Inf. Syst. 1987, 1, 119–136. [Google Scholar] [CrossRef]
 Goodchild, M. Twenty years of progress: GIScience in 2010. J. Spat. Inf. Sci. 2015, 1, 3–20. [Google Scholar] [CrossRef]
 Liang, J.; Gong, J.; Li, Y. Realistic rendering for physically based shallow water simulation in Virtual Geographic Environments (VGEs). Ann. GIS 2015, 21, 301–312. [Google Scholar] [CrossRef]
 Liu, P.; Gong, J.; Yu, M. Graphics processing unitbased dynamic volume rendering for typhoons on a virtual globe. Int. J. Dig. Earth. 2015, 8, 431–450. [Google Scholar] [CrossRef]


Category  Intended for  Product  Model Format Support 

lowlevel graphics application programming interfaces (API)  providing direct access to GPU rendering pipeline.  OpenGL  no builtin support for any model format. 
DirectX  builtin support only for its native model format.  
highlevel 3D CAD studio  creating 3D models and serving photorealistic offline rendering.  Autodesk 3ds Max  native support for various 3D model formats 
Sketchup  native support for various 3D model formats.  
intermediatelevel integrated software development kit (SDK)  accelerating development of integrated 3D applications.  OGRE  builtin support only for its native model format. 
OpenSceneGraph  support for various 3D model formats and LOD structures. 
Variable  Value 

R  86.60253906 
shadownLen  100 
height  135.3553391 
width  100 
length  346.4101563 
left  −50 
right  50 
bottom  –67.67766953 
top  67.67766953 
dist  346.4101563 
near  173.2050781 
far  519.6152344 
vForward  { 0, –0.707106781, 0.707106781} 
vUp  { 0, 0.707106781, 0.707106781} 
vCenter  { 0, 50, –50} 
Building ID  3D Measurement (m)  2D Measurement (m)  Difference (m) 

1  12.507777  13.125066  0.617289 
2  13.713325  13.732419  0.019094 
3  14.129196  14.155275  0.026079 
4  16.866035  16.933496  0.067461 
5  17.225675  17.833031  0.607356 
6  18.953028  18.25633  –0.696698 
7  18.758588  18.653542  –0.105046 
8  19.039177  19.47366  0.434483 
9  20.484453  19.157041  –1.327412 
10  20.829912  20.002697  –0.827215 
11  20.874955  21.008558  0.133603 
12  20.955293  20.958611  0.003318 
13  22.353933  22.861286  0.507353 
14  22.754253  22.423482  –0.330771 
15  22.520097  22.066294  –0.453803 
16  23.235158  24.293483  1.058325 
17  33.576494  31.089237  –2.487257 
18  37.405119  36.844787  –0.560332 
19  55.114582  54.690003  –0.424579 
20  56.291389  56.197712  –0.093677 
© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CCBY) license (http://creativecommons.org/licenses/by/4.0/).
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Liang, J.; Gong, J.; Liu, J.; Zou, Y.; Zhang, J.; Sun, J.; Chen, S. Generating Orthorectified MultiPerspective 2.5D Maps to Facilitate Web GISBased Visualization and Exploitation of Massive 3D City Models. ISPRS Int. J. GeoInf. 2016, 5, 212. https://doi.org/10.3390/ijgi5110212
Liang J, Gong J, Liu J, Zou Y, Zhang J, Sun J, Chen S. Generating Orthorectified MultiPerspective 2.5D Maps to Facilitate Web GISBased Visualization and Exploitation of Massive 3D City Models. ISPRS International Journal of GeoInformation. 2016; 5(11):212. https://doi.org/10.3390/ijgi5110212
Chicago/Turabian StyleLiang, Jianming, Jianhua Gong, Jin Liu, Yuling Zou, Jinming Zhang, Jun Sun, and Shuisen Chen. 2016. "Generating Orthorectified MultiPerspective 2.5D Maps to Facilitate Web GISBased Visualization and Exploitation of Massive 3D City Models" ISPRS International Journal of GeoInformation 5, no. 11: 212. https://doi.org/10.3390/ijgi5110212