330
Views
8
CrossRef citations to date
0
Altmetric
Articles

Accuracy test of point-based and object-based urban building feature classification and extraction applying airborne LiDAR data

&
Pages 710-730 | Received 27 Mar 2013, Accepted 07 Aug 2013, Published online: 06 Dec 2013

References

  • Antonarakis AS, Richards KS, Brasington J. 2008. Object-based land covers classification using airborne LiDAR. Remote Sens. Environ. 112:2988–2998.
  • Axelsson P. 1999. Processing of laser scanner data – algorithms and applications. ISPRS J Photogramm Remote Sens. 54:138–147.
  • Axelsson P. 2000. DEM generation from laser scanner data using adaptive TIN models. Int Arch Photogram Remote Sens Spatial Inform Sci. XXXIII:110–117.
  • Bartels M, Wei H, Mason DC. 2006. DTM Generation from LIDAR Data using Skewness Balancing. 18th International Conference on Pattern Recognition, I: 566–569.
  • Binaghi E, Gallo I, Pepe M. 2003. A neural adaptive model for feature extraction and recognition in high resolution remote sensing imagery. Int J Remote Sens. 24:3947–3959.
  • Blaschke T. 2010. Object-based image analysis for remote sensing. ISPRS J Photogram Remote Sens. 65:2–16.
  • Brennan R, Webster TL. 2006. Object-oriented lands cover classification of LiDAR derived surfaces. Can J Remote Sens. 32:62–172.
  • Briese C, Pfeifer N, Dorninger P. 2002. Applications of the Robust Interpolation for DTM determination. IAPRSIS. XXXIV/3A:55–61.
  • Charaniya AP, Manduchi R, Lodha SK. 2004. Supervised parametric classification of aerial LiDAR data. In: CVPRW’04, Proceedings of the IEEE 2004 Conference on Computer Vision and Pattern Recognition Workshop; 27 June–2 July 2004; Baltimore, MD.
  • Doucette P, Agouris P, Stefanidis A, Musavi M. 2001. Self-organized clustering for road extraction in classified imagery. J Photogram Remote Sens. 55:347–358.
  • Doucette P, Agouris P, Stefanidis A. 2004. Automated road extraction from high resolution multispectral imagery. J Photogram Eng Remote Sens. 70:1405–1416.
  • Filin S. 2002. Surface clustering from airborne laser scanning data. Int Arch Photogram Remote Sens Spatial Inform Sci. XXXIV:119–124.
  • Gamba P, Houshmand B. 2002. Joint analysis of SAR, LIDAR and aerial imagery for simultaneous extraction of land cover, DTM and 3D shape of buildings. Int J Remote Sens. 23:4439–4450.
  • Grebby S, Naden J, Cunningham D, Tansey K. 2011. Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain. Remote Sens Environ. 115:214–226.
  • Guo L, Chehata N, Mallet C, Boukir S. 2011. Relevance of airborne lidar and multispectral image data for urban scene classification using Random Forests. ISPRS J Photogram Remote Sens. 66:56–66.
  • Huang X, Zhang L, Gong W. 2011. Information fusionof aerial images and LIDAR data in urban areas: vector-stacking, re-classification and post-processing approaches. Int J Remote Sens. 32:69–84.
  • Jang JD, Payan V, Viau AA, Devost A. 2008. The use of airborne lidar for orchard tree inventory. Int J Remote Sens. 29:1767–1780.
  • Kabolizade M, Ebadi H, Ahmadi S. 2010. An improved snake model for automatic extraction of buildings from urbanaerial images and LiDAR data. Comput Environ Urban Sys. 34:435–441.
  • Kabolizade M, Ebadi H, Mohammadzadeh A. 2012. Design and implementation of an algorithm for automatic 3D reconstruction of building models using genetic algorithm. Int J Appl Earth Obs Geoinf. 19:104–114.
  • Kim K, Shan J. 2011. Building roof modeling from airborne laser scanning data based on level set approach. ISPRS J Photogram Remote Sens. 66:484–497.
  • Kraus K, Pfeifer N. 1998. Determination of terrain models in wooded areas with aerial laser scanner data. ISPRS J Photogramm Remote Sens. 53:193–203.
  • Kwak D, Lee W, Lee J, Biging GS, Gong P. 2007. Detection of individual trees and estimation of tree height using LiDAR data. J Forest Res. 12:425–434.
  • Lee H, Slatton KC, Roth BE, Cropper WP Jr. 2010. Adaptive clustering of airborne LiDAR data to segment individual treecrowns in managed pine forests. Int J Remote Sens. 31:117–139.
  • Li H, Gu H, Han Y, Yang J. 2007. Fusion of high-resolution aerial imagery and LIDAR data for object-oriented urban land-cover classification based on SVM. ISPRS workshop on updating geo-spatial databases with imagery & The 5th ISPRS workshop on DMGISs, Urumchi, China.
  • Lodha S, Kreps E, Helmbold D, Fitzpatrick D. 2006. Aerial LiDAR data classification using support vector machines (SVM). In: Third International Symposium on 3D data processing, visualization and transmission: 2, 6.
  • Lodha SK, Fitzpatrick DM, Helmbold DP. 2007. Aerial LiDAR data classification using expectation-maximization. In: Proceedings of SPIE–The International Society for Optical Engineering, SPIE.
  • Maas HG. 1999. The potential of height texture measures for the segmentation of airborne laser scanner data. In: Proceedings of the Fourth International Airborne Remote Sensing Conference, Ottawa, Canada: 154–161.
  • Medina Consultants. 2008. LiDAR campaign final report for Erie County Corridors & Niagara County. Washington (DC): US FEMA (Federal Emergency Management Agency), Available from: http://www.fema.gov/media-library.
  • Meng X, Currit N, Wang L. 2008. Morphology-based building detection from airborne LIDAR data. ASPRS 2008 Annual Conference, Portland, Oregon. April 28–May 2, 2008: 432–442.
  • Okagawa M. 2001. Algorithm of multiple filter to extract DSM from LiDAR data. In: Proceedings of 2001 ESRI International User Conference, ESRI, San Diego, CA, USA.
  • Oude Elberink S, Maas HG. 2000. The use of anisotropic height texture measures for the segment of airborne laser scanner data. Int Arch Photogram Rem Sens. 33:678–684
  • Peng J, Zhang D, Liu Y. 2005. An improved snake model for building detection from urban aerial images. Pattern Recognit Lett. 26:587–595.
  • Pfeifer N, Stadler P, Briese C. 2001. Derivation of digital terrain models in the SCOP++ environment. In: Proceedings of OEEPE workshop on airborne laserscanning and interferometric SAR for detailed digital terrain models; Stockholm, Sweden.
  • Pontil M, Verri A. 1998. Properties of support vector machines. Neural Comput. 10:955–974.
  • Sithole G. 2001. Filtering of laser altimetry data using a slope adaptive filter. Int Arch Photogram Remote Sens. 34:203 –410.
  • Sithole G, Vosselman G. 2003. Comparison of filtering algorithms. In: Proceedings of the ISPRS working group WG III/3 workshop on 3-D reconstruction from airborne lasers canner and InSAR data- XXXIV-3/W13, 8–10 October 2003; Germany: Dresden: 71–78.
  • Tang T, Zhao W, Gong H, Zhang A, Pan JG, Liu ZQ. 2008. Terrestrial laser scan (LiDAR) survey and 3D TIN model construction of urban buildings in a geospatial database. Geocarto Int. 23:259–272.
  • Vapnik VN. 1995. The nature of statistical learning theory. Berlin (Germany): Springer-Verlag. ISBN 0-387-98780-0.
  • Vosselman G. 2000. Slope based filtering of laser altimetry data. Int Arch Photogram Remote Sens. XXXIII:958–964.
  • Yang X. 2005. Use of LIDAR elevation data to construct a high-resolution digital terrain model for an estuarine marsh area. Int J Remote Sens. 26:5163–5166.
  • Zhang K, Whitman D. 2005. Comparison of three algorithms for filtering airborne LIDAR data. Photogrammetric Eng Remote Sens. 71:313–324.
  • Zhang K, Chen S, Whitman D, Shyu M, Yan J, Zhang C. 2003. A progressive morphological filter for removing non-ground measurements from airborne LIDAR data. IEEE Trans Geosci Remote Sens. 41:872–882.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.