Enhanced Autocorrelation-Based Algorithms for Filtering Airborne Lidar Data over Urban Areas
Publication: Journal of Surveying Engineering
Volume 142, Issue 2
Abstract
Many existing algorithms for light detection and ranging (lidar) data classification are known to perform reliably; however, the automation of the classification of complex urban scenes is still a challenging problem. In this paper, two classification algorithms based on spatial autocorrelation statistics, such as the Local Moran’s I and the Getis-Ord Gi*, are proposed. These autocorrelation statistics are computed over sample urban areas, including complex terrain with diverse building characteristics. The proposed autocorrelation-based algorithms are applied to airborne lidar point clouds over the complex urban areas to generate highly accurate digital elevation models (DEMs) and classify the lidar points as ground and nonground points by using the DEMs. It is also demonstrated that the minimum-based rasterization and slope-based filtering can be integrated to effectively remove outliers from the DEMs. The test results showed that the autocorrelation-based algorithms produce high-level assessment of overall classification accuracy and Cohen’s kappa index as well as a low level of total errors in complex urban scenes.
Get full access to this article
View all available purchase options and get full access to this article.
References
Anderson, E. S., Thompson, J. A., and Austin, R. E. (2005). “LIDAR density and linear interpolator effects on elevation estimates.” Int. J. Remote Sens., 26(18), 3889–3900.
Anselin, L. (1995). “Local indicators of spatial association—LISA.” Geog. Anal., 27(2), 93–115.
Axelsson, P. (1999). “Processing of laser scanner data—algorithms and applications.” ISPRS J. Photogramm. Remote Sens., 54(2), 138–147.
Axelsson, P. (2000). “DEM generation from laser scanner data using adaptive TIN models.” Int. Arch. Photogramm. Remote Sens., 33(B4/1), 111–118.
Bater, C. W., and Coops, N. C. (2009). “Evaluating error associated with lidar-derived DEM interpolation.” Comput. Geosci., 35(2), 289–300.
Brovelli, M. A., and Cannata, M. (2004). “Digital terrain model reconstruction in urban areas from airborne laser scanning data: the method and an example for Pavia (northern Italy).” Comput. Geosci., 30(4), 325–331.
Chehata, N., David, N., and Bretar, F. (2008). “LIDAR data classification using hierarchical K-means clustering.” Int. Arch. Photogramm. Remote Sens., 37(Part B3b), 325–330.
Chen, Z., Devereux, B., Gao, B., and Amable, G. (2012). “Upward-fusion urban DTM generating method using airborne Lidar data.” ISPRS J. Photogramm. Remote Sens., 72(Aug), 121–130.
Cliff, A. D., and Ord, K. (1970). “Spatial autocorrelation: A review of existing and new measures with applications.” Econ. Geogr., 46, 269–292.
Cohen, J. (1960). “A coefficient of agreement for nominal scales.” Educ. Psychol. Meas., 20(1), 37–46.
Cramer, D., Brown, A., and Hu, G. (2012). “Predicting 911 calls using spatial analysis.” Software engineering research, management and applications 2011, R. Lee, ed., Springer, Berlin, 15–26.
Dovich, R. A. (1992). Quality engineering statistics, ASQS Quality Press, Milwaukee.
Elmqvist, M. (2002). “Ground surface estimation from airborne laser scanner data using active shape models.” Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., 34(3/A), 114–118.
Elmqvist, M., Jungert, E., Lantz, F., and Persson, A. (2001). “Terrain modelling and analysis using laser scanner data.” Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., 34(3/W4), 219–226
Estornell, J., Ruiz, L. A., Velázquez-Martí, B., and Hermosilla, T. (2011). “Analysis of the factors affecting LiDAR DTM accuracy in a steep shrub area.” Int. J. Digital Earth, 4(6), 521–538.
Filin, S. (2002). “Surface clustering from airborne laser scanning data.” Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., 34(3/A), 119–124.
Fisher, P. (1995). Innovations in GIS, Taylor & Francis, London.
Forlani, G., and Nardinocchi, C. (2007). “Adaptive filtering of aerial laser scanning data.” Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., 36(3/W52), 130–135.
Getis, A., and Ord, J. K. (1992). “The analysis of spatial association by use of distance statistics.” Geogr. Anal., 24(3), 189–206.
Getis, A., and Ord, J. K. (1996). “Local spatial statistics: An overview.” Spatial analysis: Modelling in a GIS environment, P. Longley, M. Batty, eds., Wiley, New York, 374.
Green, E., Strawderman, W., and Airola, T. (1993). “Assessing classification probabilities for thematic maps.” Photogramm. Eng. Remote Sens., 59(5), 635–639.
ISPRS (International Society for Photgrammetry). (2003). “WG III/3: 3D reconstruction from airborne laser scanner and InSAR data.” ISPRS test on extracting DEMs from point clouds: A comparison of existing automatic filters. 〈http://www.itc.nl/ISPRSWGIII-3/filtertest/〉 (Jan. 15, 2015).
Kottegoda, N. T., and Rosso, R. (2009). Applied statistics for civil and environmental engineers, John Wiley & Sons, Singapore.
Lee, J.-H., Biging, G. S., Radke, J. D., and Fisher, J. B. (2013). “An improved topographic mapping technique from airborne lidar: application in a forested hillside.” Int. J. Remote Sens., 34(20), 7293–7311.
Li, Y., Wu, H., Xu, H., An, R., Xu, J., and He, Q. (2013). “A gradient-constrained morphological filtering algorithm for airborne LiDAR.” Opt. Laser Technol., 54(Dec), 288–296.
Lloyd, C. D. (2010). Local models for spatial analysis, Taylor & Francis, Boca Raton, FL.
Meng, X., Currit, N., and Zhao, K. (2010). “Ground filtering algorithms for airborne LiDAR data: A review of critical issues.” Remote Sens., 2(3), 833–860.
Meng, X., Wang, L., Silván-Cárdenas, J. L., and Currit, N. (2009). “A multi-directional ground filtering algorithm for airborne LIDAR.” ISPRS J. Photogramm. Remote Sens., 64(1), 117–124.
Mitchell, A. (2005). The ESRI guide to GIS analysis, volume 2: Spatial measurements and statistics, Esri Press, Redlands, CA.
Mongus, D., and Žalik, B. (2012). “Parameter-free ground filtering of LiDAR data for automatic DTM generation.” ISPRS J. Photogramm. Remote Sens., 67, 1–12.
Montgomery, D. C., Runger, G. C., and Hubele, N. F. (2011). Engineering statistics, John Wiley and Sons, New York.
Paradis, E. (2009). Moran’s autocorrelation coefficient in comparative methods.” R Foundation for Statistical Computing, Vienna, Austria.
Pfeifer, N., Stadler, P., and Briese, C. (2001). “Derivation of digital terrain models in the SCOP++ environment.” Proc., 2001, OEEPE Workshop on Airborne Laser Scanning and Interferometric SAR for Detailed Digital Elevation Models, Stockhold, Sweden.
Pingel, T. J., Clarke, K. C., and McBride, W. A. (2013). “An improved simple morphological filter for the terrain classification of airborne LIDAR data.” ISPRS J. Photogramm. Remote Sens., 77, 21–30.
Roggero, M. (2001). “Airborne laser scanning-clustering in raw data.” Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., 34(3/W4), 227–232.
Sharma, M., Paige, G. B., and Miller, S. N. (2010). “DEM development from ground-based LiDAR data: a method to remove non-surface objects.” Remote Sens., 2(11), 2629–2642.
Shirowzhan, S., and Lim, S. (2014). “Autocorrelation statistics-based algorithms for automatic ground and non-ground classification of Lidar data.” Proc., 31st Int. Symp. on Automation and Robotics in Construction and Mining (ISARC 2014), International Association for Automation and Robotics in Construction, Sydney, Australia, 897–902.
Sithole, G. (2001). “Filtering of laser altimetry data using a slope adaptive filter.” Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., 34(3/W4), 203–210.
Sithole, G., and Vosselman, G. (2004). “Experimental comparison of filter algorithms for bare-Earth extraction from airborne laser scanning point clouds.” ISPRS J. Photogramm. Remote Sens., 59(1–2), 85–101.
Van Genderen, J., and Lock, B. (1977). “Testing land-use map accuracy.” Photogramm. Engineering Remote Sens., 43(9), 1135–1137.
Vosselman, G. (2000). “Slope based filtering of laser altimetry data.” Int. Arch. Photogramm. Remote Sens., 33(B3/2), 935–942.
Zhang, K., Chen, S.-C., Whitman, D., Shyu, M.-L., Yan, J., and Zhang, C. (2003). “A progressive morphological filter for removing nonground measurements from airborne LIDAR data.” IEEE Trans. Geosci. Remote Sens., 41(4), 872–882.
Information & Authors
Information
Published In
Journal of Surveying Engineering
Volume 142 • Issue 2 • May 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Apr 16, 2014
Accepted: Jul 1, 2015
Published online: Dec 16, 2015
Published in print: May 1, 2016
Discussion open until: May 16, 2016
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.