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Verification and updating of the Database of Topographic Objects with geometric information about buildings by means of airborne laser scanning data

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Airborne laser scanning data (ALS) are used mainly for creation of precise digital elevation models. However, it appears that the informative potential stored in ALS data can be also used for updating spatial databases, including the Database of Topographic Objects (BDOT10k). Typically, geometric representations of buildings in the BDOT10k are equal to their entities in the Land and Property Register (EGiB). In this study ALS is considered as supporting data source. The thresholding method of original ALS data with the use of the alpha shape algorithm, proposed in this paper, allows for extraction of points that represent horizontal cross section of building walls, leading to creation of vector, geometric models of buildings that can be then used for updating the BDOT10k. This method gives also the possibility of an easy verification of up-to-dateness of both the BDOT10k and the district EGiB databases within geometric information about buildings. For verification of the proposed methodology there have been used the classified ALS data acquired with a density of 4 points/m2. The accuracy assessment of the identified building outlines has been carried out by their comparison to the corresponding EGiB objects. The RMSE values for 78 buildings are from a few to tens of centimeters and the average value is about 0,5 m. At the same time for several objects there have been revealed huge geometric discrepancies. Further analyses have shown that these discrepancies could be resulted from incorrect representations of buildings in the EGiB database.
Rocznik
Tom
Strony
22--37
Opis fizyczny
Bibliogr. 30 poz., rys., tab., wykr.
Twórcy
  • Institute of Geodesy, University of Lower Silesia, Wagonowa St. 1, 53-609 Wroclaw
autor
  • Institute of Geodesy and Geoinformatics, Wroclaw University of Environmental and Life Sciences, Grunwaldzka St. 53, 50-357 Wroclaw
Bibliografia
  • [1] Albers, B., Kada, M. & Wichmann, A. (2016). Automatic extraction and regularization of building outlines from airborne LiDAR point cloud. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI(B3), 555-560
  • [2] Bachofer, F. & Hochschild, V. (2015). A SVM-based approach to extract building footprints from Pléiades satellite imagery. The address: https://www.geotechrwanda2015.com/wp-content/uploads/2015/12/61_Felix-Bachofer.pdf
  • [3] Borkowski A. & Jóźków, G. (2012). Accuracy Assessment of Building Models Created from Laser Scanning Data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXIX-B3, 253-258, DOI: 10.5194/isprsarchives-XXXIX-B3-253-2012
  • [4] Burdeos, M.D., Makinano-Santillan, M. & Amora A.M. (2015). Automated building footprints extraction form DTM and DSM in ArcGIS. The address: http://publications.ccgeo.info/Paper_2015_36thACRS_THP3-59.pdf
  • [5] Cheng, L., Gong, J., Chen, X. & Han, P. (2008). Building boundary extraction from high resolution imagery and LiDAR data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVII (B3b), 693-698
  • [6] Edelsbrunner, H., Kirkpatrick, David G. & Seidel, R. (1983). On the shape of a set of points in the plane. IEEE Transactions on Information Theory 29 (4), 551–559
  • [7] Fayed, M. & Mouftah H.T. (2009). Localised alpha-shape computations for boundary recognition in sensor network. Ad Hoc Networks. 7, 1259-1269, DOI:10.1016/j.adhoc.2008.12.001
  • [8] Gotlib, D. (2013). Ogólna koncepcja, cel budowy i zakres informacyjny BDOT10k i BDOO, In: Olszewski R., Gotlib D. Rola bazy danych obiektów topograficznych w tworzeniu infrastruktury informacji przestrzennej w Polsce. Warszawa. Główny Urząd Geodezji i Kartografii, pp. 51-57
  • [9] Grigillo, D. & Kanjir, U. (2012). Urban object extraction from digital surface model and digital aerial images. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. I-3, 215-220
  • [10] Hauglin, M. & Næsset, E. (2016). Detection and segmentation of small trees in the forest-tundra ecotone using airborne laser Canning. Remote Sensing, 8(407), -15.
  • [11] Jarząbek-Rychard, M. & Borkowski, A. (2016). 3D building reconstruction from ALS data using unambiguous decomposition into elementary structures. The ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 118, 1-12, DOI:10.1016/j.isprsjprs.2016.04.005
  • [12] Matikainen, L., Hyyppä, J.A, Markelin, L., Kaartinen, H. & Kaartinen, H. (2010). Automatic detection of buildings and changes in buildings for updating of maps. Remote Sensing, Vol. 2, 1217-1248
  • [13] Martin, K., Pengson, LTO, Bernandez, G., Sinnaco, MJ, Soriano, MRS & Pascua, CS. (2014). Building footprint extraction and tree removal in LiDAR-derived digital elevation models. The address:http://www.a-a-r-s.org/acrs/administrator/components/com_jresearch/files/publications/TU1-5-3.pdf
  • [14] Mathworks.(2013).The address: http://www.mathworks.com/matlabcentral/fileexchange/28851-alpha-shapes, funkcja alphavol.m, autor: Jonas Lundgren (access: 20.12.2013)
  • [15] Mendela, M. (2015). Metodyka aktualizacji Bazy Danych Obiektów Topograficznych z wykorzystaniem danych lotniczego skaningu laserowego. The address: http://www.dbc.wroc.pl/dlibra/docmetadata?id=29887&from=publication
  • [16] Nex, F., Rupnik, E. & Remondino, F. (2013). Building footprints extraction from oblique imagery. ISPRS Journal of Photogrammetry and Remote Sensing, II-3/W3, 61-66
  • [17] Orthuber, E. & Avbelj, J. (2015). 3D building re construction from LiDAR point clouds by adaptive dual contouring. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. II-3/W4, 157-164
  • [18] Pawłuszek, K. & Borkowski, A. (2016). Landslides identification using airborne laser scanning data derived topographic terrain attributes and support vector machine classification. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLI-B8, 145-149, DOI:10.5194/isprsarchives-XLI-B8-145-2016
  • [19] Poloprutský, Z., Cejpová, M. & Němcová, J. (2016). Non-destructive survey of archeological sites using airborne laser scanning and geophysical applications. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences,Vol. XLI-B5, 371-376
  • [20] Rottensteiner, F. & Briese, C. (2002). A new method for building extraction in urban areas from high-resolution LiDAR data. The International Archives of Photogrammetry and Remote Sensing, XXXIV(3A), 295-301
  • [21] Rottensteiner, F. (2008). Automated updating of building data bases from digital surface models and multi-spectral images: potential and limitations. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVII (B3a), 265-270
  • [22] Tomljenovic, I., Höfle, B., Tiede, D. & Blaschke, T. (2015). Building extraction from airborne laser scanning data: an analysis of the state of the art. Remote Sensing, 7(4), 3826-3862
  • [23] Viterbi, A.J. (1967). Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Transactions on Information Theory, Vol. 13 (2), 260–269.
  • [24] Vosselman, G., Gorte, B.G.H. & Sithole, G. (2004). Change detection for updating medium scale maps using laser altimetry. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXV(B3), 207-212
  • [25] Wang, J., Lehrbass, B. & Zeng, Ch. (2011). Urban mapping using LiDAR and relief-corrected colour-infrared aerial images. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXIV, 1-4
  • [26] Wei, S. (2014). Delineation of building footprint outlines derived from vertical structures in airborne LiDAR point clouds. The address: https://www.itc.nl/library/papers_2014/msc/gfm/sun.pdf
  • [27] Wei, S. (2008). Building boundary extraction based on lidar point clouds data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVII (B3b), 157-162
  • [28] Yuan, J. (2016). Automatic building extraction in aerial scenes using convolutional networks. arXiv:1602.06564
  • [29] Zhang, K., Yan, J., Chen, Schu-Ch. (2006). Automatic construction of building footprints from airborne LiDAR data. IEEE Transactions on Geoscience and Remote Sensing, Vol.44 (9), 2523-2533
  • [30] Zhao, J., You, S. & Huang, J. ( 2011). Rapid extraction and updating of road network from airborne LiDAR data. Proceedings of IEEE Applied Imagery Pattern Recognition Workshop (AIPR),1–7
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b3601252-3788-48b3-99df-bfa637c6bc05
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