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Generating dem from lidar data – comparison of available software tools

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In recent years many software tools and applications have appeared that offer procedures, scripts and algorithms to process and visualize ALS data. This variety of software tools and of “point cloud” processing methods contributed to the aim of this study: to assess algorithms available in various software tools that are used to classify LIDAR “point cloud” data, through a careful examination of Digital Elevation Models (DEMs) generated from LIDAR data on a base of these algorithms. The works focused on the most important available software tools: both commercial and open source ones. Two sites in a mountain area were selected for the study. The area of each site is 0.645 sq km. DEMs generated with analysed software tools ware compared with a reference dataset, generated using manual methods to eliminate non ground points. Surfaces were analysed using raster analysis. Minimum, maximum and mean differences between reference DEM and DEMs generated with analysed software tools were calculated, together with Root Mean Square Error. Differences between DEMs were also examined visually using transects along the grid axes in the test sites.
Słowa kluczowe
Rocznik
Tom
Strony
271--284
Opis fizyczny
Bibliogr. 26 poz.
Twórcy
  • Department. of Geographical Information Systems, Cartography and Remote Sensing, Institute of Geography and Spatial Management, Jagiellonian University, Gronostajowa Stret, Cracow
autor
  • MGGP Aero Sp. z o.o
Bibliografia
  • 1.Anders, N., Seijmonsbergen, H., 2008. Laser altimetry and terrain analysis. A revolution in geomophology. GIM International, 22(11), pp. 36-39.
  • 2.Axelsson, P., 2000. DEM generation from laser scanner data using adaptive TIN models. The International Archives of Photogrammetry and Remote Sensing. 33/B4/1, pp. 110-117.
  • 3.Brovelli, M.A., Cannata, M., Longoni, U.M., 2002. Managing and processing LIDAR data within GRASS. Proc. GRASS Users Conference, University of Trento, Trento, Italy.
  • 4.Canopy Fuel Estimator – CFE Fuel characterization using airborne laser scan data, http://forsys.cfr.washington.edu/JFSP06/lidar_&_ifsar_tools.htm (accessed 14 Apr. 2011)
  • 5.Chase, A.F., Chase, D.Z., Weishampel, J.F., Drake, J.B., Shrestha, R.L., Slatton, K.C., Awe, J.J., Carter, W.E., 2011. Airborne LIDAR, archeology, and the ancient Maya landscape at Caracol, Belize. Journal of Archeological Science, 38(2011), pp. 387-398.
  • 6.Devereux, B.J., Amable, G.S., Crow, P., Cliff, A.D, 2005. The potential of airborne LIDAR for detection of archeological features under woodland canopies. Antiquity, 79(305), pp. 648-660.
  • 7.Dudzinska-Nowak, J., 2007. Suitability of laser scanning in the southern Baltic coastal zone research. Archives of Photogrammetry, Cartography and Remote Sensing, 17(a), pp. 179-187.
  • 8.Fernandez, J.C., Singhania, J., Caceres, K.C., Slatton, K.C., Starek, M., Kumar, R., 2007. GEM Center Report No. Rep_2007-12-001, An overview of LIDAR point cloud processing software, Gainesville, USA. http://www.aspl.ece.ufl.edu/reports/GEM_Rep_2007_12_001.pdf (accessed 18 Apr. 2011).
  • 9.Hejmanowska, B., Borowiec, N., Badurska, M., 2008. Airborne LIDAR data processing for Digital Surface Model and Digital Terrain Model generation. Archives of Photogrammetry, Cartography and Remote Sensing, 18, pp 151-162.
  • 10.Kenward, T., Lettenmaier, D.P., Wood, E.F., Fielding, E., 2000. Effects of Digital Elevation Model accuracy on hydrological predictions. Remote Sensing of Environment, 74(3), pp. 432-444.
  • 11.Kraus, K., Pfeifer, N., 2001. Advanced DEM generation from LIDAR data. The International Archives of Photogrammetry and Remote Sensing. 33/3/W4, pp. 23-30.
  • 12.Liu, X., Petersen, J., Zhang, Z., 2005. High-resolution DEM generated form LIDAR data for water resource management, Centre for GIS, Monash, Australia.
  • 13.Rayburg, S., Thoms, M., Neave, M., 2009. A comparison of Digital Elevation Models generated from different data sources. Geomorphology. 106, pp. 261-270.
  • 14.Riley, M.A., 2009. Automated detection of prehistoric conical burial mounds from LIDAR bare earth Digital Elevation Models. A thesis presented to the Department of Geology and Geography in candidacy for the degree of Master of Science, North Missouri State University Maryville, Missouri, MO, USA.
  • 15.SAGA – User’s Guide for SAGA, http://leaseweb.dl.sourceforge.net/project/sagagis/SAGA%20%20Documentation/SAGA%202%20User%20Guide/SAGA_User_Guide_Vol2_Cimmery_version_2.0.5_20101209.pdf (accessed 13 Apr. 2011).
  • 16.Shan, J., Toth, C.K., 2008. Topographic laser ranging and scanning. Principles and processing. CRC Press, Boca Raton, pp. 1-593.
  • 17.Sithole, G., Vosselman, G., 2003. Automatic structure detection in a point cloud of an urban landscape. Proceedings of 2nd Jont Workshop on Remote Sensing and Data Fusion over urban Areas (Urban 2003), Berlin, Germany, pp. 67-71.
  • 18.Sithole, G., Vosselman, G., 2004. Experimental comparison of filter algorithm for bare- Earth extraction from airborne laser scanning point clouds. ISPRS Journal of Photogrammetry and Remote Sensing. 59, pp. 85-101.
  • 19.Snyder, N.P., 2009. Studying stream morphology with airborne laser elevation data. EOS, 6(90), pp. 45-52.
  • 20.TerraScan User’s Guide, http://www.terrasolid.fi/system/files/tscan_2.pdf(accessed 15 Apr. 2011)
  • 21.TLID User’s Guide – available with software license, http://www.tiltanse.co.il/page.asp?cat=197&type=2&lang=2 (accesed 5 Dec. 2011).
  • 22.Tymków, P., Borkowski, A., 2006. The use of airborne laser scanning data to land cover supervised classification for hydrodynamic modelling. Archives of Photogrammetry, Cartography and Remote Sensing, 16, pp. 537-546.
  • 23.Wang, C.K., Tseng, Y.H., 2010. DEM generation from airborne LIDAR data by an adaptive dual-directional slope filter. In: ISPRS TC VII Symposium – 100 Years ISPRS, Vienna, Austria, Vol. XXXVIII, Part 7B, pp. 628-632.
  • 24.Weed C., 2000. Generate Digital Elevation Models using laser altimetry (LIDAR) data. Final Report EE 381K, Multidimensional Digital Signal Processing, Center for Space Research, Austin, TX, USA.
  • 25.Wężyk, P., Borowiec, N., Szombara, S., Wanczak, R., 2008. Generation of Digital surface and terrain models of the tatras mountains based on airborne laser scanning (ALS) point cloud. Archives of Photogrammetry, Cartography and Remote Sensing, 18, pp. 651-661.
  • 26.Vosselman, G., 2000. Slope based filtering of laser altimetry data. IAPRS, WG III/3, 33/B3, pp. 935-942.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fab667c2-5999-4425-b194-188c76e4d201
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