Deriving ground surface digital elevation models from LiDAR data with geostatistics

International Journal of Geographical Information Science

Volumn 20, Issue 5, 2006, Pages 535-563

  Lloyd, Christopher ^a   Atkinson, Peter M ^b  

^a QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

DEM; Kriging; LiDAR

Indexed keywords

DIGITAL ELEVATION MODEL; GEOSTATISTICS; KRIGING; LIDAR;

EID: 33646767135     PISSN: 13658816     EISSN: 17417546     Source Type: Journal    
DOI: 10.1080/13658810600607337     Document Type: Article

References (36)

1. Armstrong, M. (1998). In Basic Linear Geostatistics. Berlin: Springer.
2. Beckers, F. and Bogaert, P. (1998) Nonstationarity of the mean and unbiased variogram estimation: Extension of the weighted least squares method. Mathematical Geology, 30, pp. 223-240.
3. Campbell, J. B. (2002). In Introduction to Remote Sensing third. London: Taylor & Francis.
4. Chilès, J. P. and Delfiner, P. (1999). In Geostatistics: Modeling Uncertainty. New York: John Wiley and Sons.
5. Christensen, R. (1993) Quadratic covariance estimation and equivalence of predictions. Mathematical Geology, 25, pp. 541-558.
6. Cressie, N. A. C. (1991). In Statistics for Spatial Data. New York: John Wiley and Sons.
7. Cressie, N. A. C. and Zimmerman, D. L. (1992) On the stability of the geostatistical method. Mathematical Geology, 24, pp. 45-59.
8. Curran, P. J. (1988) The semivariogram in remote sensing: An introduction. Remote Sensing of Environment, 24, pp. 493-507.
9. Curran, P. J. and Atkinson, P. M. (1998) Geostatistics in remote sensing. Progress in Physical Geography, 22, pp. 61-78.
10. Deutsch, C. V. and Journel, A. G. (1998). In GSLIB: Geostatistical Software Library and User's Guide. New York: Oxford University Press. second edition
11. Doucette, P. and Beard, K. (2000) Exploring the capability of some GIS surface interpolators for DEM gap fill. Photogrammetric Engineering and Remote Sensing, 66, pp. 881-888.
12. Goovaerts, P. (1997). In Geostatistics for Natural Resources Evaluation. New York: Oxford University Press.
13. Isaaks, E. H. and Srivastava, R. M. (1989). In An Introduction to Applied Geostatistics. New York: Oxford University Press.
14. Jaafar, J. and Priestnall, G. and Mather, P. M. and Vieira, C. A. (1999) Construction of DEM from LiDAR DSM using morphological filtering, conventional statistical approaches and artificial neural networks. In RSS 99. Earth Observation: From Data to Information. (pp. 299-306). Nottingham: Remote Sensing Society.
15. Johnston, K. and Ver Hoef, J. M. and Krivoruchko, K. and Lucas, N. (2001). In Using ArcGIS™ Geostatistical Analyst. Redlands CA: ESRI.
16. Journel, A. G. and Huijbregts, C. J. (1978). In Mining Geostatistics. London: Academic Press.
17. Kitanidis, P. K. (1993) Generalized covariance functions in estimation. Mathematical Geology, 25, pp. 525-540.
18. Kraus, K. (1997) Restitution of airborne laser scanner data in wooded areas. In EARSeL Advances in Remote Sensing. Yearbook 1997. (pp. 120-127). Paris: EARSeL.
19. Kraus, K. and Pfeifer, N. (1998) Determination of terrain models in wooded areas with airborne laser scanner data. ISPRS Journal of Photogrammetry and Remote Sensing, 53, pp. 193-202.
20. Lillesand, T. M. and Kiefer, R. W. (2000). In Remote Sensing and Image Interpretation 4. New York: Wiley.
21. Lloyd, C. D. and Atkinson, P. M. (2002a) Deriving DSMs from LiDAR data with kriging. International Journal of Remote Sensing, 23, pp. 2519-2524.
22. Lloyd, C. D. and Atkinson, P. M. (2002b) Non-stationary approaches for mapping terrain and assessing uncertainty in predictions. Transactions in GIS, 6, pp. 17-30.
23. Lohr, U. (1998) Digital elevation models by laser scanning. Photogrammetric Record, 16, pp. 105-109.
24. Matheron, G. (1971). In The Theory of Regionalised Variables and its Applications. Fontainebleau: Centre de Morphologie Mathématique de Fontainebleau.
25. Olea, R. A. (1975). In Optimum Mapping Techniques Using Regionalized Variable Theory. Lawrence: University of Kansas. Kansas University Geological Survey Series on Spatial Analysis No.2
26. Olea, R. A. (1977). In Measuring Spatial Dependence with Semivariograms. Lawrence: University of Kansas. Kansas University Geological Survey Series on Spatial Analysis No.3
27. Pebesma, E. J. and Wesseling, C. G. (1998) Gstat, a program for geostatistical modelling, prediction and simulation. Computers and Geosciences, 24, pp. 17-31.
28. Reutebuch, S. E. and McGaughey, R. J. and Andersen, H.-E. and Carson, W. W. (2003) Accuracy of a high-resolution LiDAR terrain model under a conifer forest canopy. Canadian Journal of Remote Sensing, 29, pp. 527-535.
29. Rossi, R. and Dungan, J. and Beck, L. R. (1994) Kriging in the shadows: geostatistical interpolation for remote sensing. Remote Sensing of Environment, 49, pp. 32-40.
30. Samberg, A. (1997) What laser scanning can do today: Current techniques. In EARSeL Advances in Remote Sensing. Yearbook 1997. (pp. 114-119). Paris: EARSeL.
31. Todd, K. W. and Csillag, F. and Atkinson, P. M. (2003) Three-dimensional mapping of light transmittance and foliage distribution using LiDAR. Canadian Journal of Remote Sensing, 29, pp. 544-555.
32. Wackernagel, H. (2003). In Multivariate Geostatistics. An Introduction with Applications third. Berlin: Springer.
33. Webster, R. and Burgess, T. M. (1980) Optimal interpolation and isarithmic mapping of soil properties. III. Changing drift and universal Kriging. Journal of Soil Science, 31, pp. 505-524.
34. Wehr, U. and Lohr, U. (1999a) Airborne laser scanning - an introduction and overview. ISPRS Journal of Photogrammetry and Remote Sensing, 54, pp. 68-82.
35. Wehr, U. and Lohr, U. (1999b) Theme issue on airborne laser scanning. ISPRS Journal of Photogrammetry and Remote Sensing, 54, pp. 61-63.
36. Wise, S. (2002). In GIS Basics. London: Taylor & Francis.