access icon free Accuracy assessment of airborne laser scanner dataset by means of parametric and non-parametric statistical methods

Parametric and non-parametric statistical methods are compared and discussed for the accuracy assessment of digital surface models coming from airborne laser scanner. Such datasets are chosen from different types of areas: from the relatively favourable flat terrain to the complex built-up areas and abrupt terrain zones with vegetation. For those complex sites, a reference ‘ground truth’ is established using a mobile mapping system, whereas flat terrain areas are checked through static ground surveying using global positioning system. The experimental results confirm that systematic errors and many outliers remain in the airborne laser scanner dataset corresponding to built-up and abrupt terrain areas, and thus that nonparametric statistical methods are suitable for an accuracy assessment.

Inspec keywords: Global Positioning System; geophysical image processing; digital elevation models; terrain mapping; vegetation mapping; statistical analysis

Other keywords: accuracy assessment; parametric statistical methods; digital surface models; airborne laser scanner dataset; nonparametric statistical methods; global positioning system; mobile mapping system; flat terrain areas; vegetation

Subjects: Geophysical aspects of vegetation; Other topics in statistics; Satellite communication systems; Other topics in statistics; Geography and cartography computing; Probability theory, stochastic processes, and statistics; Data and information; acquisition, processing, storage and dissemination in geophysics; Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research; Other topics in Earth sciences; Optical, image and video signal processing; Computer vision and image processing techniques

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
      • 33. Chavuenet, W.: ‘A manual of spherical and practical astronomy’, 1863.
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
      • 19. Karel, W., Pfeifer, N., Briese, C.: ‘Dtm quality assessment’. ISPRS Commission II Symp., 2006.
    10. 10)
    11. 11)
    12. 12)
      • 27. D'Agostino, R.B., Belanger, A., D'Agostino, R.B.: ‘A suggestion for using powerful and informative tests of normality’, Am. Stat., 1990, 44, (4), pp. 316321.
    13. 13)
      • 25. Kolmogorov, A.N.: ‘Sulla determinazione empirica di una legge di distribuzione’, G. dell'Istituto Italiano degli Attuari, 1933, 4, (1), pp. 8391.
    14. 14)
      • 31. Horng-Jinh, C., Kuo-Chung, H., Chao-Hsien, W.: ‘Determination of sample size in using central limit theorem for Weibull distribution’, Int. J. Inf. Manage. Sci., 2006, 17, (3), pp. 3146.
    15. 15)
    16. 16)
      • 15. Maune, D.F.: ‘Digital elevation model technologies and applications: the dem user manual’, (American Society for Photogrammetry and Remote Sensing, ASPRS, 2007).
    17. 17)
    18. 18)
      • 10. Li, Z.: ‘Effects of check points on the reliability of dtm accuracy estimates obtained from experimental tests’, Photogramm. Eng. Remote Sens., 1991, 57, (10), pp. 13331340.
    19. 19)
      • 37. Mood, A., Graybill, F.: ‘Introduction to the Theory of Statistics’ (McGraw-Hill, 1974, 3rd edn)..
    20. 20)
      • 24. D'Agostino, R.B.: ‘Tests for the normal distribution’, in Stephens, M., D'Agostino, R. (Eds.): ‘Goodness-of-fit techniques’ (Marcel Dekker, 1986).
    21. 21)
    22. 22)
    23. 23)
    24. 24)
      • 39. Wilcox, R.R.: ‘Introduction to robust estimation and hypothesis testing’ (Academic Press San Diego, 1997).
    25. 25)
    26. 26)
    27. 27)
    28. 28)
      • 32. BIPM, IEC, IFCC, ISO, IUPAC, IUPAP, OIML: ‘Evaluation of measurement data guide to the expression of uncertainty in measurement(JCGM, 2008) pp. 1120.
    29. 29)
    30. 30)
    31. 31)
      • 14. Federal Geodetic Control Committee: ‘Standards and specifications for geodetic control networks’. National Geodetic Information Center, 1984.
    32. 32)
      • 36. Efron, B., Tibshirani, R.: ‘An introduction to the bootstrap’ (Chapman & Hall/CRC, 1993).
    33. 33)
    34. 34)
    35. 35)
    36. 36)
    37. 37)
      • 26. Smirnov, N.: ‘On the estimation of the discrepancy between empirical curves of distribution for two independent samples’, Bull. Math. de l'Univer. de Moscow, 1939, 2, pp. 314.
    38. 38)
    39. 39)
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