Analysis of oblique aerial images for land cover and point cloud classification in an Urban environment

IEEE Transactions on Geoscience and Remote Sensing

Volumn 53, Issue 3, 2015, Pages 1304-1319

  Rau, Jiann Yeou ^a   Jhan, Jyun Ping ^a   Hsu, Ya Ching ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Object based image analysis (OBIA); oblique aerial image; point cloud classification

Indexed keywords

AERIAL PHOTOGRAPHY; ANTENNAS; CLASSIFICATION (OF INFORMATION); IMAGE CLASSIFICATION; OBJECT DETECTION; OBJECT RECOGNITION; PHOTOGRAMMETRY; REMOTE SENSING; ROOFS; SEMANTICS; URBAN PLANNING;

AERIAL IMAGES; CLASSIFICATION ACCURACY; CLASSIFICATION SCHEME; OBJECT BASED IMAGE ANALYSIS; OBJECT BASED IMAGE ANALYSIS (OBIA); POINT CLOUD; SEMANTIC CLASSIFICATION; SPECTRAL CHARACTERISTICS;

STEREO IMAGE PROCESSING;

ACCURACY ASSESSMENT; AERIAL PHOTOGRAPH; HIERARCHICAL SYSTEM; IMAGE ANALYSIS; IMAGE CLASSIFICATION; LAND COVER; PHOTOGRAMMETRY; SPECTRAL ANALYSIS; THREE-DIMENSIONAL MODELING; URBAN ATMOSPHERE;

EID: 84907522905     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2014.2337658     Document Type: Article

References (77)

1. A. S. Antonarakis, K. S. Richards, and J. Brasington, "Object-based land cover classification using airborne LiDAR," Remote Sens. Environ., vol. 112, no. 6, pp. 2988-2998, Jun. 2008.
2. F. Rottensteiner et al., "Results of the ISPRS benchmark on urban object detection and 3D building reconstruction," ISPRS J. Photogramm. Remote Sens., vol. 93, pp. 256-271, Jun. 2014.
3. F. Rottensteiner, J. Trinder, S. Clode, and K. Kubik, "Building detection by fusion of airborne laser scanner data and multi-spectral images: Performance evaluation and sensitivity analysis," ISPRS J. Photogramm. Remote Sens., vol. 62, no. 2, pp. 135-149, Jun. 2007.
4. N. Haala and M. Kada, "An update on automatic 3D building reconstruction," ISPRS J. Photogramm. Remote Sens., vol. 65, pp. 570-580, 2010.
5. G. Sithole and G. Vosselman, "Report: ISPRS Comparison of Filters," Delft Univ. Technol., Delft, The Netherlands, Oct. 10, 2003.
6. J. Secord and A. Zakhor, "Tree detection in urban regions using aerial lidar and image data," IEEE Geosci. Remote Sens. Lett., vol. 4, no. 2, pp. 196-200, Apr. 2007.
7. M. A. Lefsky et al., "Lidar remote sensing of the canopy structure and biophysical properties of Douglas-FirWestern Hemlock forests," Remote Sens. Environ., vol. 70, no. 3, pp. 339-361, Dec 1999.
8. M. A.Wulder et al., "Lidar sampling for large-area forest characterization: A review," Remote Sens. Environ., vol. 121, pp. 196-209, Jun. 2012.
9. H. Tang et al., "Deriving and validating Leaf Area Index (LAI) at multiple spatial scales through lidar remote sensing: A case study in Sierra National Forest, CA," Remote Sens. Environ., vol. 143, pp. 131-141, Mar. 2014.
10. W. L. Stefanov, M. S. Ramsey, and P. R. Christensen, "Monitoring urban land cover change: An expert system approach to land cover classification of semiarid to arid urban centers," Remote Sens. Environ., vol. 77, pp. 173-185, 2001.
11. M. Gerke and N. Kerle, "Automatic structural seismic damage assessment with airborne oblique pictometry imagery," Photogramm. Eng. Remote Sens., vol. 77, pp. 885-898, 2011.
12. X. Yang, Urban Remote Sensing: Monitoring, Synthesis and Modeling in the Urban Environment. Hoboken, NJ, USA: Wiley, 2011, p. 408.
13. U. Heiden et al., "Urban structure type characterization using hyperspectral remote sensing and height information," Landscape Urban Plan., vol. 105, no. 4, pp. 361-375, Apr. 2012.
14. M. A. Carlberg, P. Gao, G. Chen, and A. Zakhor, "Urban landscape classifcation system using airborne LiDAR," in Proc. Int. Conf. Image Process., 2009, pp. 1-9.
15. M. Gerke and J. Xiao, "Fusion of airborne laserscanning point clouds and images for supervised and unsupervised scene classification," ISPRS J. Photogramm. Remote Sens., vol. 87, pp. 78-92, Jan. 2014.
16. F. Lafarge and C. E. Mallet, "Creating large-scale city models from 3D-point clouds-A robust approach with hybrid representation," Int. J. Comput. Vis., vol. 99, no. 1, pp. 69-85, Aug. 2012.
17. J. Niemeyer, F. Rottensteiner, and U. Soergel, "Classification of urban LiDAR data using conditional random field and random forests," in Proc. JURSE, São Paulo, Brazil, 2013, pp. 139-142.
18. G. Forlani, C. Nardinocchi, M. Scaioni, and P. Zingaretti, "Complete classification of raw LIDAR data and 3D reconstruction of buildings," Pattern Anal. Appl., vol. 8, no. 4, pp. 357-374, Feb. 2006.
19. P. Dorninger and N. Pfeifer, "A comprehensive automated 3D approach for building extraction, reconstruction, and regularization from airborne laser scanning point clouds," Sensors, vol. 8, no. 11, pp. 7323-7343, 2008.
20. C. Alexander, S. Smith-Voysey, C. Jarvis, and K. Tansey, "Integrating building footprints and LiDAR elevation data to classify roof structures and visualise buildings," Comput. Environ. Urban Syst., vol. 33, no. 4, pp. 285-292, Jul. 2009.
21. N. Haala and C. Brenner, "Virtual city models from laser altimeter and 2D map data," Photogramm. Eng. Remote Sens., vol. 65, no. 7, pp. 787-795, Jul. 1999.
22. G. Wei et al., "Multi-wavelength canopy LiDAR for remote sensing of vegetation: Design and system performance," ISPRS J. Photogramm. Remote Sens., vol. 69, pp. 1-9, Apr. 2012.
23. F. Rottensteiner et al., "The ISPRS benchmark on urban object classification and 3D builiding reconstruction," in Proc. ISPRS Ann. Photogramm., Remote Sens. Spatial Inf. Sci., Melbourne, Australia, 2012, pp. 1-6.
24. Z. Qin, W. Li, M. Li, Z. Chen, and G. Zhou, "A methodology for true orthorectification of large-scale urban aerial images and automatic detection of building occlusions using digital surface model," in Proc. IEEE Int. Geosci. Remote Sens. Symp., Toulouse, France, Jul. 2003, pp. 729-731.
25. J. Y. Rau, N. Y. Chen, and L. C. Chen, "True orthophoto generation of built-up areas using multi-view images," Photogramm. Eng. Remote Sens., vol. 68, no. 6, pp. 581-588, Jun. 2002.
26. A. F. Habib, E. M. Kim, and C. J. Kim, "New methodologies for true orthophoto generation," Photogramm. Eng. Remote Sens., vol. 73, no. 1, pp. 25-36, Jan. 2007.
27. M. Gerke and J. Xiao, "Supervised and unsupervised MRF based 3D scene classification in multiple view airborne oblique images," in Proc. ISPRS Ann. Photogramm., Remote Sens. Spatial Inf. Sci.:CMRT13-City Models, Roads Traffic, Antalya, Turkey, 2013, pp. 25-30.
28. P. Mishra, E. Ofek, and G. Kimchi, "Validation of vector data using oblique images," in Proc. 16th ACM SIGSPATIAL Int. Conf. Adv. Geographic Inf. Syst., Irvine, CA, USA, 2008, pp. 5-7.
29. F. Ackermann, "Airborne laser scanning-Present status and future expectations," ISPRS J. Photogramm. Remote Sens., vol. 54, no. 2/3, pp. 64-67, Jul. 1999.
30. M. Huber,W. Schickler, S. Hinz, and A. Baumgartner, "Fusion of LIDAR data and aerial imagery for automatic reconstruction of building surfaces," in Proc. 2nd GRSS/ISPRS Joint Workshop Remote Sens. Data Fusion over Urban Areas, May 2003, pp. 82-86.
31. C. Strecha, T. Tuytelaars, and L. V. Gool, "Dense matching of multiple wide-baseline views," in Proc 19th IEEE Int. Conf. Comput. Vis., Oct. 2003, pp. 1194-1201.
32. H. Hirschmuller, "Stereo vision in structured environments by consistent semi-global matching," in Proc. IEEE Conf. CVPR, New York, NY, USA, 2006, pp. 2386-2393.
33. M. Gerke, "Dense matching in high resolution oblique airborne images," in Proc. CMRT, IAPRS, Paris, France, 2009, pp. 77-82.
34. N. Haala, "The landscape of dense image matching algorithms," in Proc. Photogramm. Week, Berlin, Germany, 2013, pp. 271-284, Offenbach.
35. A. H. Ahmadabadian et al., "A comparison of dense matching algorithms for scaled surface reconstruction using stereo camera rigs," ISPRS J. Photogramm. Remote Sens., vol. 78, pp. 157-167, Apr. 2013.
36. Y. Furukawa and J. Ponce, "Accurate, dense, and robust multiview stereopsis," IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 8, pp. 1362-1376, Aug. 2010.
37. V. H. Hiep, R. Keriven, P. Labatut, and J. P. Pons, "Towards highresolution large-scale multi-view stereo," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., Miami, FL, USA, 2009, pp. 1430-1437.
38. A. R. Dick, P. H. S. Torr, and R. Cipolla, "Modelling and interpretation of architecture from several images," Int. J. Comput. Vis., vol. 60, no. 2, pp. 111-134, Nov. 2004.
39. Y. Furukawa, B. Curless, S. Seitz, and R. Szeliski, "Manhattan-world stereo," in Proc. IEEE Conf. Comput. Vis. Pattern Recog, Miami, FL, USA, 2009, pp. 1422-1429.
40. Y. Furukawa, B. Curless, S. M. Seitz, and R. Szeliski, "Towards Internetscale multi-view stereo," in Proc. IEEE Conf. CVPR, San Francisco, CA, USA, 2010, pp. 1434-1441.
41. M. Rothermel, K. Wenzel, D. Fritsch, and N. Haala, "SURE: Photogrammetric surface reconstruction from imagery," in Proc. LC3D Workshop, Berlin, Germany, 2012, pp. 1-9.
42. A. M. Hamruni, "The use of Oblique and Vertial Images for 3D Urban Modeling," Ph.D. dissertation, Dept. Civil Eng., University of Nottingham, Nottingham, U.K, 2010.
43. C. Frueh, R. Sammon, and A. Zakhor, "Automated texture mapping of 3D city models with oblique aerial imagery," in Proc. 2nd Int. Symp. 3D Data Process., Vis., Transmiss., 2004, pp. 396-403.
44. G. J. Grenzdörffer, M. Guretzki, and I. Friedlander, "Photogrammetric image acquisition and image analysis of oblique imagery," Photogramm. Rec., vol. 23, no. 124, pp. 372-386, Dec. 2008.
45. U. S. Panday, "Fitting of Parametric Building Models to Oblique Aerial Images," M.S. thesis, Faculty Geo-Inf. Sci. Earth Observ., Univ. Twente, Enschede, The Netherlands, 2011.
46. A. Fischer, T. H. Kolbe, and F. Lang, "On the use of geometric and semantic models for component-based building reconstruction," in Proc. SMATI Images Maps, W. Forstner, C.-E. Liedtke, and J. Buckner, Eds., München, 1999, pp. 101-120.
47. K. Kulschewski and K. R. Koch, "Recognition of buildings using a dynamic Bayesian network," in Proc. SMATI Images Maps, W. Forstner, C.-E. Liedtke, and J. Buckner, Eds., München, Germany, 1999, pp. 121-132.
48. J. Xiao, M. Gerke, and G. Vosselman, "Building extraction from oblique airborne imagery based on robust facade detection," ISPRS J. Photogramm. Remote Sens., vol. 68, pp. 56-68, Mar. 2012.
49. A. P. Nyaruhuma, M. Gerke, and G. Vosselman, "Evidence of walls in oblique images for automatic verificatin of buildings," in Proc. IAPRS, Saint-Mandé, France, 2010, pp. 263-268.
50. A. P. Nyaruhuma, M. Gerke, and G. Vosselman, "Line matching in oblique airborne images to support automatic verification of building outlines," in Proc. ASPRS Annu. Conf., San Diego, CA, USA, 2010, 12 p.
51. A. K. Rasika, N. Kerle, and S. Heuel, Multi-Scale Texture and Color Segmentation of Oblique Airborne Video Data for Damage Classification, 2006.
52. D. Lu and Q. Weng, "A survey of image classification methods and techniques for improving classification performance," Int. J. Remote Sens., vol. 28, no. 5, pp. 823-870, Feb. 2007.
53. P. Gamba, F. Dell'Acqua, and B. V. Dasarathy, "Urban remote sensing using multiple data sets: Past, present, and future," Inf. Fusion, vol. 6, no. 4, pp. 319-326, Dec. 2005.
54. S.W. Myint, P. Gober, A. Brazel, S. Grossman-Clarke, and Q. Weng, "Perpixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery," Remote Sens. Environ., vol. 115, no. 5, pp. 1145-1161, May 2011.
55. M. Herold and J. Scepan, "Object-oriented mapping and analysis of urban land use/cover using IKONOS data," in Proc. 22nd Earsel Symp. Geoinf. Eur.-Wide Integr., Rotterdam, The Netherlands, 2003, pp. 1-8, Millpress.
56. R. Pu, S. Landry, and Q. Yu, "Object-based urban detailed land cover classification with high spatial resolution IKONOS imagery," Int. J. Remote Sens., vol. 32, no. 12, pp. 3285-3308, Jun. 2011.
57. W. Zhou, G. Huang, A. Troy, and M. L. Cadenasso, "Object-based land cover classification of shaded areas in high spatial resolution imagery of urban areas: A comparison study," Remote Sens. Environ., vol. 113, no. 8, pp. 1769-1777, Aug. 2009.
58. T. Blaschke, "Object based image analysis for remote sensing," ISPRS J. Photogramm. Remote Sens., vol. 65, no. 1, pp. 2-16, Jan. 2010.
59. I. A. Rizvi and B. K. Mohan, "Object-based image analysis of highresolution satellite images using modified cloud basis function neural network and probabilistic relaxation labeling process," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 12, pp. 4815-4820, Dec. 2011.
60. Y. Lina, Z. Guifeng, and W. Zhaocong, "A scale-synthesis method for high spatial resolution remote sensing image segmentation," IEEE Trans. Geosci. Remote Sens., vol. 50, no. 10, pp. 4062-4070, Oct. 2012.
61. C. Burnett and T. Blaschke, "A multi-scale segmentation/object relationship modeling methodology for landscape analysis," Ecol. Model., vol. 168, no. 3, pp. 233-249, Oct. 2003.
62. T. Blaschke et al., "Geographic object-based image analysis-Towards a new paradigm," ISPRS J. Photogramm. Remote Sens., vol. 87, pp. 180-191, Jan. 2014.
63. J. Barlow, Y. Martin, and S. Franklin, "Detecting translational landslide scars using segmentation of Landsat ETM+ and DEM data in the northern Cascade Mountains, British Columbia," Can. J. Remote Sens., vol. 29, no. 4, pp. 510-517, 2003.
64. D. Marr, Vision: A Computational Approach. San Francisco, CA, USA: Freeman, 1982.
65. A. S. Laliberte and A. Rango, "Texture and scale in object-based analysis of subdecimeter resolution unmanned aerial vehicle (UAV) imagery," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 3, pp. 761-770, Mar. 2009.
66. L. Drągut and T. Blaschke, "Automated classification of landform elements using object-based image analysis," Geomorphology, vol. 81, no. 3/4, pp. 330-344, Nov. 2006.
67. S. Katz, A. Tal, and R. Basri, "Direct visibility of point sets," ACM Trans. Graph., vol. 26, no. 3, pp. 1-11, Jul. 2007.
68. P. Axelsson, "Processing of laser scanner data-Algorithms and applications," ISPRS J. Photogramm. Remote Sens., vol. 54, pp. 138-147, 1999.
69. M. Wang and Y.-H. Tseng, "Incremental segmentation of lidar point clouds with an octree-structured voxel space," Photogramm. Rec., vol. 26, no. 133, pp. 32-57, Mar. 2011.
70. R. M. Haralick, K. Shanmugam, and I. Dinstien, "Textural features for image classification," IEEE Trans. Syst., Man Cybern., vol. SMC-3, no. 6, pp. 610-621, Nov. 1973.
71. B. J. Devereux, G. S. Amable, and C. C. Posada, "An efficient image segmentation algorithm for landscape analysis," Int. J. Appl. Earth Observ. Geoinf., vol. 6, pp. 47-61, 2004.
72. M. Baatz and A. Schape, "Multiresolution segmentation: An optimization approach for high quality multi-scale image segmentation," in Angewandte Geographische Informations verar beitung XII. Beiträge zum AGIT-Symposium Salzburg. Berlin, Germany: Herbert Wichmann Verlag.
73. R. Mathieu, J. Aryal, and A. K. Chong, "Object-based classification of IKONOS imagery for mapping large-scale vegetation communities in urban areas," Sensors, vol. 7, no. 11, pp. 2860-2880, 2007.
74. B. Salehi, Y. Zhang, M. Zhong, and V. Dey, "Object-based classification of urban areas using VHR imagery and height points ancillary data," Remote Sens., vol. 4, no. 8, pp. 2256-2276, 2012.
75. R. Kohavi and F. Provost, "Glossary of terms," Mach. Learn., vol. 30, pp. 271-274, 1998.
76. M. Rutzinger, F. Rottensteiner, and N. Pfeifer, "A comparison of evaluation techniques for building extraction from airborne laser scanning," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 2, no. 1, pp. 11-20, Mar. 2009.
77. J. Cohen, "A coefficient of agreement for nominal scales," Educ. Psychol. Meas., vol. 20, no. 1, pp. 37-46, 1960.