Wykrywanie budynków na podstawie lotniczego skanowania laserowego

• Autorzy: Bucior M. , Borowiec N.; , Jędrychowski I. , Pyka K.

Warianty tytułu

EN

Detection of buildings based on airborne laser scanning data

• Języki publikacji: PL

Abstrakty

EN

This paper discusses automatic detection of buildings from airborne laser scanner data. Beside introduction and conclusions there are three main parts in this paper. In part one basic technical parameters of airborne laser scanning are reminded. Part two presents literature review of various methods that have been applied in the detection and modeling of buildings. Part three describes a research experiment carried out by the authors. This part includes a comparison between two methods of detection: the one offered by specialist software and the alternative method proposed by the authors of this paper. The technique of laser scanning, often referred to as LIDAR, continues to develop very dynamically. It is characterized by a high level of efficiency and accuracy. It is most often used to create 3D models of cities. Until now, LIDAR was mostly used in national studies to determine digital terrain models (DTM), which is done by separating certain points (those which result from laser reflections of trees, buildings and other above-ground surfaces) from disorganized .clouds of points.. Meanwhile, the most useful contribution of this technique is that it enables numeric calculation of the digital surface model (DSM). The authors. experiment attempted to analyze the effectiveness of automatic detection of buildings using two different methods. The first method used original data and applied specialist software which detects and models buildings. In the second, the .cloud of points. was replaced by a regular grid, which had been determined through interpolation. Then, using the typical tool of GIS, the authors carried out a series of experiments. In this paper, the authors present their concept of detection of buildings. This concept is based on an analysis of three surface layers: map of heights, map of slopes and map of texture. The final stage consisted of spatial analysis which showed all the places which meet certain conditions that are adequate for buildings, such as heights, slopes and texture. The methods were implemented on two test areas. One area contained independently standing apartment buildings in which the sides and rooftops of buildings were perpendicular and at right angles to each other. The second test area was made up of various buildings of differentiated heights with steep, multidirectional roofs. For both these areas, reference data was obtained through the vectorization of photogrammetric stereoscopic models. Both methods of detection showed comparable effectiveness. The method using .cloud of points. and specialist software showed slightly straighter roof edges, however a slightly worse balance of surface in relation to the reference data, than the method based on GIS analyses which presents the authors. concepts of detections of buildings. However, the differences were negligible and both methods had a similar level of effectiveness in the detection of buildings: approximately 90% for the easy area and about 60% for difficult area. These results are similar to those presented in literature. During the study, all cases in which detection of buildings was ineffective were also analyzed. Tall trees rising above rooftops often presented a significant obstacle. Moreover, the scanning data contained several places, where LIDAR provided measurements with very low density, much smaller than the average density of 1,5 points per m2. These .holes. lowered the effectiveness of the first method. However, the weakness of the raster method was weak representation of the grid in places where trees were located as the applied interpolation smoothed out the original data. The results of this research lead to the conclusion that an optimal method would entail a .combined. approach. First, the raster analysis should be applied to determine the probable location of buildings. Then, for certain atypical spaces one should return to the source data (cloud of points) and vertically assign cross sections in predefined directions. What is still needed is a method of automatic recognition of buildings on the basis of cross sections as well as dimensions of buildings which aim to obtain a 3D model. This paper confirms a huge potential of the laser scanning technique to create 3D models. The proposed method of detection of buildings proved promising and it can be applied even without expensive specialized software.

Słowa kluczowe

PL

laser; skanowanie; wykrywanie budynków; modelowanie budynków

EN

laser; scanning; building detection; building modelling

• Wydawca: Polskie Towarzystwo Informacji Przestrzennej
• Czasopismo: Roczniki Geomatyki
• Rocznik: 2006
• Tom: T. 4, z. 3
• Strony: 57--70
• Opis fizyczny: Bibligr. 38 poz.

Twórcy

autor

Bucior M.

autor

Borowiec N.;

autor

Jędrychowski I.

autor

Pyka K.

• Akademia Górniczo-Hutnicza,

Bibliografia

• 1. Ahokas, Kaarttinen, Hyyppä J., 2005: EuroSDR Building Extraction comparison. Final Report.
• 2. Ameri B., 2000: Automatic Recognition and 3D Reconstruction of Buildings from Digital Imagery. PhD Thesis, Institute of Photogrammetry, Stuttgart University, DGK-C 526. 32 (3/1), pp. 400-408.
• 3. Axelsson P., 1999: Processing of laser scanner data . algorithms and applications. ISPRS Journal of Photogrammetry & Remote Sensing 54, 138-147.
• 4. Baltsavias E.P.,1999a: Airborne laser scanning: existing systems and firms and other resources, ISPRS Journal of Photogrammetry & Remote Sensing 54 (1999).164.198.
• 5. Baltsavias E.P.,1999b: Airborne laser scanning: basic relations and formulas. ISPRS Journal of Photogrammetry & Remote Sensing 54 (1999).199.214.
• 6. Baltsavias E.P., 2004. Object extraction and revision by image analysis using existing geodata and knowledge: current status and steps towards operational systems. ISPRS Journal of Photogrammetry and Remote Sensing, 58(3-4): 129-151.
• 7. Borkowski A., 2003: Modelowanie powierzchni terenu zawierającej linie nieciągłości na podstawie danych skaningu laserowego. Archiwum Fotogrametrii, Kartografii i Teledetekcji, vol.13B, 307-314.
• 8. Borkowski A., 2005: Filtracja danych lotniczego skaningu laserowego z wykorzystaniem metody aktywnych powierzchni. Roczniki Geomatyki 2005, t. III z. 4. 35-42.
• 9. Bucior M., 2006: Wykrywanie budynków na podstawie lotniczego skaningu laserowego. Praca magisterska, AGH, Wydział Geodezji Górniczej Inżynierii środowiska.
• 10. Brenner C., 2000: Towards fully automatic generation of city models. IAPRS 33 (B3), 85-92.
• 11. Brenner C., 2001: City models - automation in research and practise. Photogrammetric Week´01, pp. 149-158.
• 12. Cho W., Jwa Y.S., Chang H.J., Lee S.H., 2004: Pseudo-grid Based Building Extraction Using Airborne Lidar Data, ISPRS, Comm. 3.
• 13. Crosilla F., Visintini D., Prearo G., 2004: A Robust Method for Filtering Non-Ground Measurements from Airborne Lidar Data. ISPRS XXth Congress Comm.3.
• 14. Crosilla F., Visintini D., Sepic F., 2005: A segmentation procedure of LiDAR data by applying mixed parametric and nonparametric models. ISPRS WG III/3, III/4, V/3 Workshop .Laser scanning 2005., Enschede.
• 15. Dworak T. Z., 1990: Metodyka teledetekcyjnych badań zapylenia atmosfery. ZN AGH, nr 1339, seria Sozologia i Sozotechnika, z. 29.
• 16. Fuchs C., 1998: Extraktion polymorpher Bildstrukturen und ihre topologische und geometrische Gruppierung. PhD Thesis, Institute of Photogrammetry, Bonn University, DGK-C 502.
• 17. Gruen, A., Baltsavias E.P., Henricsson O., 1997: Automatic Extraction of Man-Made Objects from Aerial and Space Images (II), Birkhauser Verlag.
• 18. Hyyppä J., Pyssalo U., Hyyppä H., Samberg A., 2002: Elevation accuracy of laser scanning . derived digital terrain and target models in forest environment. International Archives of Photogrammetry and Remote Sensing, Vol. XXXIV / 3A, Graz.
• 19. Kurczyński Z., 1999: Lotniczy skaner laserowy - nowa technologia pozyskiwania danych o rzeźbie terenu. Geodeta nr 2 (45).
• 20. Kurczyński Z., 2006: Lotniczy skaning laserowy (LIDAR). http://www.geoforum.pl/ (dostęp 24.07.2006).
• 21. Maas H.G., Vosselman G., 1999: Two algorithms for extracting building models from raw laser altimetry data. ISPRS Journal of Photogrammetry and Remote Sensing, 54 (2-3), pp. 153-163.
• 22. Marmol U., 2003: Pozyskanie numerycznego modelu powierzchni topograficznej (NMPT) w oparciu o dane wysokościowe pochodzące z lotniczego skanera laserowego. Archiwum Fotogrametrii, Kartografii i Teledetekcji, vol.13B, 419-426.
• 23. Marmol U., 2005: Filtrowanie danych wysokościowych pochodzących z lotniczego skanera laserowego, Rozprawa doktorska, AGH, Kraków.
• 24. Materka A., Szczypiński P., Kociołek M., Strzelecki M., 2001: Computer program for image texture analysis in PhD students laboratory, Instytut Elektroniki Politechniki Łódzkiej, 2001.
• 25. Matikainen L., Hyyppä J., Hyyppä H., 2003: Automatic detection of buildings from laser scanner data for map updating. In: IAPRSIS XXXIV / 3W13.
• 26. Mayer H., 1999: Automatic object extraction from aerial imagery - A survey focusing on buildings. Computer Vision and Image Understanding, 74(2):138-149.
• 27. Morgan M., Habib A., 2001: 3D TIN for Automatic Building Extraction from airborne Laser Scanning Data, Proceedings of the ASPRS .Gateway to the New Millennium..
• 28. Paparoditis N., Cord M., Jordan M., Cocquerez J.P., 1998: Building detection and reconstruction from midand high-resolution aerial imagery. Computer Vision and Image Understanding, 72(2).
• 29. Rudnicki Z., 2002: Wybrane metody przetwarzania i analizy cech obrazów teksturowych. Zakład Konstrukcji i Eksploatacji Maszyn, AGH, Kraków.
• 30. Rottensteiner F., 2001: Semi-automatic extraction of buildings based on hybrid adjustment using 3D surface models and management of building data in a TIS. PhD Thesis. Geowissenschaftliche Mitteilungen 56, Institute of Photogrammetry and Remote Sensing, Vienna University of Technology.
• 31. Rottensteiner, F., Briese, C., 2003. Automatic generation of building models from LIDAR data and the integration of aerial images. [In:] The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Dresden, Germany, Vol. XXXIV, Part 3/W13, pp. 174-180.
• 32. Schenk T., Csatho B., Lee D.C., 1999: Quality control issues of airborne laser ranging data and accuracy study in an urban area. Proceedings of the ISPRS Workshop . ISPRS WG III/5, WG III/2:
• 33. Schwalbe E., 2004: 3D building model generation from airborne laserscanner data by straight line detection in specific orthogonal projections, ISPRS, Commision 3.
• 34. Smith, Holland, Longley: The importance of understanding error in Lidar Digital Elevation Models, ISPRS, Commision 4, 2004.
• 35. Sohn G., Dowman I., 2002: Terrain surface reconstruction by the use of tetrahedron model with the MDL criterion. International Archives of Photogrammetry and Remote Sensing, Vol. XXXIV / 3A, 336-344, Graz.
• 36. Soininen A., 2003: TerraScan. User Guide. Terrasolid.
• 37. Wehr A., Lohr U., 1999: Airborne laser scanning-an introduction and overview, ISPRS Journal of Photogrammetry & Remote Sensing 54 (1999).68.82.
• 38. Vosselman G., Dijkman S., 2001: 3D building model reconstruction from point clouds and ground plans.IAPRS 34(3W4): 37-43.