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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-92160a1e-b137-4923-a8dc-bcbac6c79581

Czasopismo

Archiwum Fotogrametrii, Kartografii i Teledetekcji

Tytuł artykułu

A new approach to dtm error estimation basing on laplacian probability distribution function

Autorzy Hejmanowska, B.  Kay, S. 
Treść / Zawartość
Hejmanowska.pdf
Warianty tytułu
Języki publikacji EN
Abstrakty
EN A Digital Terrain Model (DTM) derived from Airborne Laser Scanning (ALS) was the subject of our research. In this paper, the vertical accuracy of the DTM was analyzed on the basis of the commonly used statistics, i.e. mean error and standard deviation, assuming a normal (Gauss) error distribution. The further approach, the so-called robust method (Höhle, Höhle 2009), was also tested, where the median was a substitute for the mean error and the Normalized Median Absolute Deviation (NMAD) for the standard deviation. An alternative method based on the Laplace function is proposed in the paper for describing the probability density function, where the parameters of the Laplace function are proposed for DTM error estimation. The test area was near the Joint Research Centre in Ispra, Italy; raw ALS data covering the test area were collected in 2005 and processed for DTM generation. Accuracy analysis was performed based on the comparison of DTM with the raw ALS data and with in-situ height measurements. The distribution of DTM errors calculated from ALS data was significantly non-normal, confirming other results reported in the literature. The Gauss distribution function considerably overestimated the vertical DTM errors; however, the robust method underestimated them. The Laplace function matched the error histograms the best, and accuracy parameters derived from this function could be considered as an alternative method for DTM accuracy evaluation.
Słowa kluczowe
PL Aerial   LIDAR   dokładność   chmura punktów   skanowanie laserowe  
EN Aerial   lidar   accuracy   point cloud   laser scanning  
Wydawca Zarząd Główny Stowarzyszenia Geodetów Polskich
Czasopismo Archiwum Fotogrametrii, Kartografii i Teledetekcji
Rocznik 2011
Tom Vol. 22
Strony 201--213
Opis fizyczny Bibliogr. 13 poz.
Twórcy
autor Hejmanowska, B.
  • University of Science and Technology, Faculty of Mine surveying and Environmental Engineering, Krakow, Poland, al. Mickiewicza 30, 30-059 Kraków, Poland, galia@agh.edu.pl
autor Kay, S.
  • European Commission JRC, Institute for Environment and Sustainability, Via Enrico Fermi 2749, I-21027 Ispra (VA), Italy, simon.kay@jrc.ec.europa.eu
Bibliografia
1.Axelson P., 2000. DEM Generation from Laser Scanner Data Using Adaptive TIN Models. International Archives of Photogrammetry and Remote Sensing, Amsterdam, Netherlands 32,B4/1, pp. 110 – 117
2.ASPRS Lidar Committee. 2004. ASPRS Guidelines Vertical Accuracy Reporting for Lidar Data, http://www.asprs.org/society/committees/lidar/downloads/vertical_accuracy_reportriangleg _for_lidar_data.pdf (accessed 7th April 2011)
3.Aguilar F.,J., Mills J.P., Delgado J., Manuel A. Aguilar M.A., Negreiros J.G., Pérez J. L. – 2010, Modelling vertical error in LiDAR-derived digital elevation models , ISPRS Journal of Photogrammetry and Remote Sensing 65 (2010) 103_110
4.Atkinson Gordo A. D. J., Ariza López F.J, José L. García-Balboa J. L. 2005 Positional accuracy control using robust estimator, In Proceedings of the 21st International Cartographic Conference, 09-16 July, Acoruna, Spain
5.Darnel A. R., Nicholas J. Tate N. J., Chris Brunsdon C., 2008 - Improving user assessment of error implications in digital elevation models, Computers, Environment and Urban Systems 32 (2008) 268–277
6.Fisher P.F., Tate N.J. 2006. Causes and consequences of error in digital elevation models. Progress in Physical Geography 30, 4, p. 467-489
7.Höhle J., Höhle M., 2009 - Accuracy assessment of digital elevation models by means of robust statistical methods, ISPRS Journal of Photogrammetry and Remote Sensing 64 (2009) 398_406
8. Höhle J. The EUROSDR project “Automated checking and improving of digital terrain models” http://www.asprs.org/publications/proceedings/tampa2007/0027.pdf (accessed 7th April 2011)
9. Hejmanowska B., Borowiec N. Badurska M. 2008 – „Processing airborne data to Digital Surface Model and Digital Terrain Model. Final report http://home.agh.edu.pl/~galia/research/Processing%20LIDAR%20%202007%20final%20re port_5_03_2008.pdf (accessed 7th April 2011)
10.Kraus K., Karel W., Briese Ch., Mandlburger G., 2006. Local Accuracy Measures for Digital Terrain Model. Photogrammetric Record 21 (116), p. 342-354
11. Oksansen J. 2006. Digitale elevation model error in terrain analysis. PhD Thesis http://ethesis.helsinki.fi/julkaisut/mat/maant/vk/oksanen/digitale.pdf (accessed 7th April 2011)
12. Wechsler S.P., 2001. DEM Uncertainty: Evaluation and Effect on Topographic Parameters. Dissertation State University of New York, College of Environmental Science and Forestry, Syracuse, New York
13. Zandbergen P. A., 2008 Positional Accuracy of Spatial Data: Non-Normal Distributions and a Critique of the National Standard for Spatial Data Accuracy, Transactions in GIS, 2008, 12(1): 103–130 ISO 19113:2002 Geographic information - Quality principles
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