Chapter 1: Introduction 1
1.5 Thesis objectives and structure 32
(1) Implement current popular building extraction methods, and develop a systematic framework to evaluate extracted building footprints thoroughly, with the focus on building shape similarity and metric redundancy removal.
(2) Develop a building height estimation method from a Digital Surface Model (DSM) derived from stereo imagery to search for building height in complicated and inaccurate DSMs.
(3) Develop an advanced building height extraction method from stereo imagery constrained by building footprints, in order to overcome the defects of current matching methods that perform poorly on dense urban areas and tall buildings. (4) Reconstruct 3D buildings and develop a new multi-criteria system to evaluate the reconstruction accuracy from different perspectives in a true 3D environment. Two study sites are employed to develop methods for different building information extraction and evaluation from remotely sensed data. The two study areas are: (a) the campus of the University of Western Ontario, London, Ontario, Canada, and (b) the campus of Beijing Normal University, Beijing, China. The reference data are ground GPS-surveyed absolute elevation and laser rangefinder-measured building relative heights.
Specifically, to investigate a building in remote sensing imagery, the first step is to identify its location. In Chapter 2, the main objective is to implement different extraction methods for building footprints and to evaluate the results in terms of accuracy. Four popular building footprint extraction methods are implemented for comparison between
different data sources. The resultant identified building location is a prerequisite for building height estimation; In Chapters 3 and 4, methods were investigate of building height extraction. In Chapter 3, a method is proposed to use popular optical satellite stereo imagery to extract building roof elevation directly. In Chapter 4, it was discussed about building ground elevation estimation based on a DSM derived from widely used commercial software and building footprints derived from the methods presented in Chapter 2; then building height can be calculated from roof and ground elevation contrast. In Chapter 5, 3D building reconstruction is discussed, and effective accuracy evaluation methods for reconstructed 3D buildings derived from a range of methods and data are explored.
References
Aguilar, M.A., Del Mar Saldana, M., & Aguilar, F.J. (2014). Generation and quality assessment of stereo-extracted DSM from geoeye-1 and worldview-2 imagery. IEEE Transactions on
Geoscience and Remote Sensing, 52(2), 1259-1271.
Ahmadi, S., Zoej, M.J.V., Ebadi, H., Moghaddam, H.A., & Mohammadzadeh, A. (2010). Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours. International Journal of Applied Earth Observation and
Geoinformation, 12(3), 150-157.
Blaschke, T. (2010). Object based image analysis for remote sensing. ISPRS Journal of
Photogrammetry and Remote Sensing, 65(1), 2-16.
Brunner, D., Lemoine, G., & Bruzzone, L. (2010). Earthquake damage assessment of buildings using VHR optical and SAR imagery. IEEE Transactions on Geoscience and Remote Sensing, 48(5), 2403-2420.
Brunner, D., Lemoine, G., Bruzzone, L., & Greidanus, H. (2010). Building height retrieval from VHR SAR imagery based on an iterative simulation and matching technique. IEEE Transactions
on Geoscience and Remote Sensing, 48(3 PART2), 1487-1504.
Champion, N., Boldo, D., Pierrot-Deseilligny, M., & Stamon, G. (2010). 2D building change detection from high resolution satelliteimagery: A two-step hierarchical method based on 3D invariant primitives. Pattern Recognition Letters, 31(10), 1138-1147.
D'Urso, G., Richter, K., Calera, A., Osann, M.A., Escadafal, R., Garatuza-Pajan, J., et al. (2010). Earth Observation products for operational irrigation management in the context of the PLEIADeS project. Agricultural Water Management, 98(2), 271-282.
Di, K., Ma, R., & Li, R. (2001, 23–27 April). Deriving 3D shorelines from highresolution Ikonos
satellite images with rational functions. Paper presented at the ASPRS Annual Conference, St
Louis, Missouri.
Di, K., Ma, R., & Li, R.X. (2003). Rational functions and potential for rigorous sensor model recovery. Photogrammetric Engineering and Remote Sensing, 69(1), 33-41.
DigitalGlobe. (2014). Satellite Overview. Retrieved Jan-12-2014, from http://www.digitalglobe.com/about-us/content-collection#overview
Forlani, G., Nardinocchi, C., Scaioni, M., & Zingaretti, P. (2006). Complete classification of raw LIDAR data and 3D reconstruction of buildings. Pattern Analysis and Applications, 8(4), 357- 374.
Gamba, P., Houshmand, B., & Saccani, M. (2000). Detection and extraction of buildings from interferometric SAR data. IEEE Transactions on Geoscience and Remote Sensing, 38(1 II), 611- 618.
Grodecki, J. (2001, 23–27 April). Ikonos stereo feature extraction—RPC approach. Paper presented at the ASPRS Annual Conference, St. Louis, Missouri.
Gröger, G., & Plümer, L. (2012). CityGML - Interoperable semantic 3D city models. ISPRS
Journal of Photogrammetry and Remote Sensing, 71, 12-33.
Gruen, A. (2012). Development and status of image matching in photogrammetry.
Photogrammetric Record, 27(137), 36-57.
Gruen, A.W. (1985). Adaptive least squares correlation: A powerful image matching technique.
South African Journal of Photogrammetry, Remote Sensing, and Cartography, 14.
Guida, R., Iodice, A., & Riccio, D. (2010). Height retrieval of isolated buildings from single high- resolution SAR images. IEEE Transactions on Geoscience and Remote Sensing, 48(7), 2967- 2979.
Haala, N., & Kada, M. (2010). An update on automatic 3D building reconstruction. ISPRS
Journal of Photogrammetry and Remote Sensing, 65(6), 570-580.
Henn, A., Gröger, G., Stroh, V., & Plümer, L. (2013). Model driven reconstruction of roofs from sparse LiDAR point clouds. ISPRS Journal of Photogrammetry and Remote Sensing, 76, 17-29. Hirschmuller, H. (2008). Stereo processing by semiglobal matching and mutual information.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(2), 328-341.
Hirschmuller, H., & Bucher, T. (2010). Evaluation of digital surface models by semi-global
matching. Paper presented at the DGPF 2010, Vienna, Austria.
Huang, H., Brenner, C., & Sester, M. (2013). A generative statistical approach to automatic 3D building roof reconstruction from laser scanning data. ISPRS Journal of Photogrammetry and
Remote Sensing, 79, 29-43.
Huertas, A., & Nevatia, R. (1988). Detecting buildings in aerial images. Computer Vision,
Graphics and Image Processing, 41(2), 131-152.
Irvin, R.B., & McKeown, D.M. (1989). Methods for exploiting the relationship between buildings and their shadows in aerial imagery. IEEE Transactions on Systems, Man and Cybernetics, 19(6), 1564-1575.
Jayaraman, V., Chandrasekhar, M.G., & Rao, U.R. (1997). Managing the natural disasters from space technology inputs. Acta Astronautica, 40(2-8), 291-325.
Kabolizade, M., Ebadi, H., & Ahmadi, S. (2010). An improved snake model for automatic extraction of buildings from urban aerial images and LiDAR data. Computers, Environment and
Urban Systems, 34(5), 435-441.
Kass, M., Witkin, A., & Terzopoulos, D. (1988). Snakes: Active contour models. International
Journal of Computer Vision, 1(4), 321-331.
Khattak, S.R., Buckstein, D.S., & Hogue, A. (2013). Reconstructing 3D Buildings from LIDAR
Using Level Set Methods. Paper presented at the International Conference on Computer and
Robot Vision (CRV), Regina, SK.
Kim, Z.W., Huertas, A., & Nevatia, R. (2001). Automatic description of buildings with complex
rooftops from multiple images. Paper presented at the IEEE Computer Society.
Kong, D., Xu, L., & Li, X. (2013). A new method for building roof segmentation from airborne LiDAR point cloud data. Measurement Science and Technology, 24(9).
Lafarge, F., Descombes, X., Zerubia, J., & Pierrot-Deseilligny, M. (2008). Automatic building extraction from DEMs using an object approach and application to the 3D-city modeling. ISPRS
Journal of Photogrammetry and Remote Sensing, 63(3), 365-381.
Lafarge, F., & Mallet, C. (2012). Creating large-scale city models from 3D-point clouds: A robust approach with hybrid representation. International Journal of Computer Vision, 99(1), 69-85. Lee, D.S., Shan, J., & Bethel, J.S. (2003). Class-guided building extraction from Ikonos imagery.
Photogrammetric Engineering and Remote Sensing, 69(2), 143-150.
Lillesand, T.M., Kiefer, R.W., & Chipman, J.W. (2008). Remote sensing and image
interpretation. Hoboken, NJ: John Wiley & Sons.
McKeown, D.M., & Cochran, S.D. (1999). Fusion of HYDICE hyperspectral data with panchromatic imagery for cartographic feature extraction. IEEE Transactions on Geoscience and
Remote Sensing, 37(3 I), 1261-1277.
Michaelsen, E., Stilla, U., Soergel, U., & Doktorski, L. (2010). Extraction of building polygons from SAR images: Grouping and decision-level in the GESTALT system. Pattern Recognition
Letters, 31(10), 1071-1076.
Pan, H., Zhang, G., Tang, X., Li, D., Zhu, X., Zhou, P., et al. (2013). Basic products of the ZiYuan-3 satellite and accuracy evaluation. Photogrammetric Engineering and Remote Sensing, 79(12), 1131-1145.
Kabolizade, M., Ebadi, H., & Ahmadi, S. (2010). An improved snake model for automatic extraction of buildings from urban aerial images and LiDAR data. Computers, Environment and
Urban Systems, 34(5), 435-441.
Kass, M., Witkin, A., & Terzopoulos, D. (1988). Snakes: Active contour models. International
Journal of Computer Vision, 1(4), 321-331.
Khattak, S.R., Buckstein, D.S., & Hogue, A. (2013). Reconstructing 3D Buildings from LIDAR
Using Level Set Methods. Paper presented at the International Conference on Computer and
Robot Vision (CRV), Regina, SK.
Kim, Z.W., Huertas, A., & Nevatia, R. (2001). Automatic description of buildings with complex
rooftops from multiple images. Paper presented at the IEEE Computer Society.
Kong, D., Xu, L., & Li, X. (2013). A new method for building roof segmentation from airborne LiDAR point cloud data. Measurement Science and Technology, 24(9).
Lafarge, F., Descombes, X., Zerubia, J., & Pierrot-Deseilligny, M. (2008). Automatic building extraction from DEMs using an object approach and application to the 3D-city modeling. ISPRS
Journal of Photogrammetry and Remote Sensing, 63(3), 365-381.
Lafarge, F., & Mallet, C. (2012). Creating large-scale city models from 3D-point clouds: A robust approach with hybrid representation. International Journal of Computer Vision, 99(1), 69-85. Lee, D.S., Shan, J., & Bethel, J.S. (2003). Class-guided building extraction from Ikonos imagery.
Photogrammetric Engineering and Remote Sensing, 69(2), 143-150.
Lillesand, T.M., Kiefer, R.W., & Chipman, J.W. (2008). Remote sensing and image
interpretation. Hoboken, NJ: John Wiley & Sons.
McKeown, D.M., & Cochran, S.D. (1999). Fusion of HYDICE hyperspectral data with panchromatic imagery for cartographic feature extraction. IEEE Transactions on Geoscience and
Remote Sensing, 37(3 I), 1261-1277.
Michaelsen, E., Stilla, U., Soergel, U., & Doktorski, L. (2010). Extraction of building polygons from SAR images: Grouping and decision-level in the GESTALT system. Pattern Recognition
Letters, 31(10), 1071-1076.
Pan, H., Zhang, G., Tang, X., Li, D., Zhu, X., Zhou, P., et al. (2013). Basic products of the ZiYuan-3 satellite and accuracy evaluation. Photogrammetric Engineering and Remote Sensing, 79(12), 1131-1145.
Pu, S., & Vosselman, G. (2009). Knowledge based reconstruction of building models from terrestrial laser scanning data. ISPRS Journal of Photogrammetry and Remote Sensing, 64(6), 575-584.
Rottensteiner, F., Sohn, G., Gerke, M., Wegner, J.D., Breitkopf, U., & Jung, J. (2013). Results of the ISPRS benchmark on urban object detection and 3D building reconstruction. ISPRS Journal
of Photogrammetry and Remote Sensing.
Sampath, A., & Shan, J. (2007). Building boundary tracing and regularization from airborne lidar point clouds. Photogrammetric Engineering and Remote Sensing, 73(7), 805-812.
Shao, Y., Taff, G.N., & Walsh, S.J. (2011). Shadow detection and building-height estimation using IKONOS data. International Journal of Remote Sensing, 32(22), 6929-6944.
Simonetto, E., Oriot, H., & Garello, R. (2005). Rectangular building extraction from stereoscopic airborne radar images. IEEE Transactions on Geoscience and Remote Sensing, 43(10), 2386- 2395.
Soergel, U., Michaelsen, E., Thiele, A., Cadario, E., & Thoennessen, U. (2009). Stereo analysis of high-resolution SAR images for building height estimation in cases of orthogonal aspect directions. ISPRS Journal of Photogrammetry and Remote Sensing, 64(5), 490-500.
Sohn, G., & Dowman, I. (2007). Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction. ISPRS Journal of Photogrammetry and Remote Sensing, 62(1), 43-63.
Sohn, G., Jwa, Y., Jung, J., & Kim, H. (2012, 25 August – 01 September 2012). An Implicit
Regularization for 3D Building Rooftop Modeling using Airborne LIDAR Data. Paper presented
at the ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Melbourne, Australia.
Stanivuk, V. (2012). Measurements of the GSM signal strength by mobile phone. Paper presented at the 20th Telecommunications Forum, TELFOR 2012 - Proceedings, Belgrade; Serbia;.
Suveg, I., & Vosselman, G. (2004). Reconstruction of 3D building models from aerial images and maps. ISPRS Journal of Photogrammetry and Remote Sensing, 58(3-4), 202-224.
Szeliski, R. (2010). Computer vision: algorithms and applications (pp. 533-577).
Tack, F., Buyuksalih, G., & Goossens, R. (2012). 3D building reconstruction based on given ground plan information and surface models extracted from spaceborne imagery. ISPRS Journal
Tao, C.V., & Hu, Y. (2001). A comprehensive study of the rational function model for photogrammetric processing. Photogrammetric Engineering and Remote Sensing, 67(12), 1347- 1357.
Tao, C.V., & Hu, Y. (2002). 3D reconstruction methods based on the rational function model.
Photogrammetric Engineering and Remote Sensing, 68(7), 705-714.
Tournaire, O., Bredif, M., Boldo, D., & Durupt, M. (2010). An efficient stochastic approach for building footprint extraction from digital elevation models. ISPRS Journal of Photogrammetry
and Remote Sensing, 65(4), 317-327.
Tupin, F., & Roux, M. (2003). Detection of building outlines based on the fusion of SAR and optical features. ISPRS Journal of Photogrammetry and Remote Sensing, 58(1-2), 71-82.
Turlapaty, A., Gokaraju, B., Du, Q., Younan, N.H., & Aanstoos, J.V. (2012). A hybrid approach for building extraction from spaceborne multi-angular optical imagery. IEEE Journal of Selected
Topics in Applied Earth Observations and Remote Sensing, 5(1), 89-100.
Vouzounaras, G., Daras, P., & Strintzis, M.G. (2011). Automatic generation of 3D outdoor and indoor building scenes from a single image. Multimedia Tools and Applications, 1-18.
Wang, R. (2013). 3D building modeling using images and LiDAR: a review. International
Journal of Image and Data Fusion, 4(4), 273-292.
Wu, B., Zhang, Y., & Zhu, Q. (2012). Integrated point and edge matching on poor textural images constrained by self-adaptive triangulations. ISPRS Journal of Photogrammetry and
Remote Sensing, 68(1), 40-55.
Zhang, K., Yan, J., & Chen, S.C. (2006). Automatic construction of building footprints from airborne LIDAR data. IEEE Transactions on Geoscience and Remote Sensing, 44(9), 2523-2533. Zhang, M., Zhang, L., Mathiopoulos, T., Xie, W., Ding, Y., & Wang, H. (2012). A geometry and texture coupled flexible generalization of urban building models. ISPRS Journal of