Scale-Dependent Effect of Input Data Design on DEM Accuracy

  • Radoslav Bonk
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Terrain geomorphometric properties are major input parameters for majority of GIS-supported topographic models and applications such as erosion-deposition model, solar radiation model (Suri and Hofierka 2005), soil erosion model or river basin modelling (De Roo et al. 2000)

Keywords

Root Mean Square Error Sampling Design Spatial Autocorrelation Terrain Complexity Digital Terrain Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Ackerman, F. (1980). The accuracy of digital terrain models. In Proceedings of the 37thPhotogrammetric Week, pages 113–143, University of StuttgartGoogle Scholar
  2. Baredo, J., Lavalle, C., and De Roo, A. P. J. (2005). European flood risk mapping. European Commission Joint Research Centre. Special Publication. S.P.I.O5.151.ENGoogle Scholar
  3. Bates, P. and De Roo, A. P. J. (2000). A simple raster-based model for flood inundation simulation. Journal of Hydrology, 236:54–77CrossRefGoogle Scholar
  4. Bonk, R. (2003). Scale-dependent impact of selected factors on morphometric parameters accuracy and automated geomorphologicalmapping. PhD thesis, Comenius University Bratislava, Slovakia, Faculty of Natural SciencesGoogle Scholar
  5. Cebecauer, T., Hofierka, J., and Suri, M. (2002). Processing digital terrain models by regularized spline with tension: tuning interpolation parameters for different input datasets. In Ciolli, M. and Zatelli, P., editors, Proceedings of the Open Source GIS — GRASS users conference 2002, Trento, Italy, 11–13 September Google Scholar
  6. Clif, A. D. and Ord, J. K. (1981). Spatial Processes: Models and Applications. London: PionGoogle Scholar
  7. De Roo, A. P. J. (2000). Modelling runoff and sediment transport in catchments using GIS. In Gurnell, A.M. and Montgomery, D.R., editors, Eydrohgical Applications of GIS, Advances in Hydrological Processes, page 184. John WileyGoogle Scholar
  8. De Roo, A. P. J., Barredo, J., Lavalle, C., Bodis, K., and Bonk, R. (2005). Potential flood hazard and risk mapping at pan-European scale. In Peckham, R. and Jordan, G., editors, Digital elevation modelling. Development and applications in a policy support environment. Joint Research Centre, European Commission, Ispra. in pressGoogle Scholar
  9. De Roo, A. P. J., Gouweleeuw, B., Thielen, J., Bates, P., and Hollings worth, A. (2003). Development of a European flood forecasting. International Journal of River Basin Management, l(l):49–59CrossRefGoogle Scholar
  10. De Roo, A. P. J., Wesseling, C., and Van Deursen, W. P. A. (2000). Physicallybased river basin modeling within a gis: The LISFLOOD model. Hydrological Processes, (14):1981–1992Google Scholar
  11. Goodchild, M. (1986). Spatial autocorrelation. In Concepts and Techniques in Modern Geography. Norwich: Geo BooksGoogle Scholar
  12. Li, Z. (1990). Sampling strategy and accuracy assessment for digital terrain modeling. PhD thesis, University of Glasgow, Glasgow. 299 pp.Google Scholar
  13. Li, Z. (1991). Effects of check points on the reliability of dtm accuracy estimates obtained from experimental tests. Photogrammetric Enineering & Remote Sensing, 57(10):1333–1340Google Scholar
  14. Li, Z. (1992). Variation of the accuracy of digital terrain models with sampling interval. Photo grammetric Records, 14(79): 113–128CrossRefGoogle Scholar
  15. Li, Z. (1994). A comparative study of the accuracy of digital terrain models (DTMs) based on various data models. ISPRS Journal of Photogrammetry and Remote Sensing, 49(1):2–11CrossRefGoogle Scholar
  16. Makarovic, B. (1972). Information transfer in construction of data from sampled data. Photogrammetria, 28(4):111–130CrossRefGoogle Scholar
  17. Minar, J. (1998). Georelief and geoecobgical mapping in large scales. PhD thesis, Dept. of Physical Geography and Geoecology, Faculty of Natural sciences, Comenius University, Bratislava. in SlovakGoogle Scholar
  18. Mitasova, H. and Hofierka, J. (1993). Interpolation by regularized spline with tension: II. Application to terrain modeling and surface geometry analysis. Mathematical Geology, 25(6):657–669CrossRefGoogle Scholar
  19. Neteler, M. and Mitasova, H. (2002). Open Source GIS: A GRASS GIS Approach. Kluver Academic Publishers. 1st.editionGoogle Scholar
  20. Schmidt, J.and Dikau, R. (1999). Extracting geomorphometric attributes and objects from digital elevation models — semantics, methods, future needs. In R. Dikau and H. Saurer, editor, GIS for Earth Surface Systems, pages 154–172. Gebrüder Borntraeger, D-14129 Berlin D-70176 StuttgartGoogle Scholar
  21. Suri, M. and Hofierka, J. (2005). Application of DEM in solar radiation modelling (natural resources: solar energy). In Peckham, R. and Jordan, G., editors, Digital elevation modelling. Development and applications in a policy support environment. Joint Research Centre, European Commission, Ispra. in pressGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Radoslav Bonk

There are no affiliations available

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