Abstract
Digital elevation models (DEM) are becoming increasingly important as tools in hydrological research and water resources management. Since error and uncertainty are inherently associated with spatial data, a complete evaluation of a DEM is of utmost importance before it is put into subsequent analysis. The present paper offers an innovative approach for quality assessment of contour interpolated DEMs of different resolutions. Five most frequently cited interpolation methods viz., TIN with linear interpolation, Inverse Distance Weighing, Thin Plate Spline, Ordinary Kriging and TOPOGRID were selected for gridding of contours at five different resolutions i.e., 30m, 45m, 60m, 75m and 90m. In order to compare the quality of interpolated DEMs, a qualitative and quantitative evaluation of inter-polated DEMs for their vertical, horizontal and shape accuracy were carried out. It was found that different interpolation methods produced DEMs with different levels of artifacts. The analyses of vertical accuracy suggested that the variations were not pronounced in nature. However, the quantitative comparisons for horizontal and shape accuracy showed that there was a high level of disparity with significant differences among the interpolated DEMs.
Similar content being viewed by others
References
Burrough PA and McDonnell RA (1998) Creating continuous surfaces from point data. In: Burrough PA, Goodchild MF, McDonnell RA, Witzer P, Worboys M (eds.), Principles of Geographic Information Systems. Oxford University Press, Oxford, UK
Darboux F, Gascuel-Odoux C and Davy P (2002) Effects of surface water storage by soil roughness on overland-flow generation. Earth Surface Processes and Landforms 27: 223–233
Desmet PJJ (1997) Effects of interpolation errors on the analysis of DEM. Earth Surface Processes and Landforms 22: 563–580
Jensen JR (1996) Introductory digital image processing: A remote sensing perspective (2nd ed.). New Jersey. Prentice — Hall
Jensen SK and Domingue JO (1988) Extracting topographic structure from digital elevation data for geographical information system analysis. Photogrammetric Engineering and Remote Sensing 54(11): 1593–1600
Kienzle SW (2004) The effect of DEM raster resolution on first order, second order and compound terrain derivatives. Transactions in GIS 8(1):83–111
Li Z (1991) Effects of checkpoints on the reliability of DTM accuracy estimates obtained from experimental tests. Photogrammetric Engineering & Remote Sensing 57(10): 1333–1340
Maune DF, editor (2001) Digital Elevation Model Technologies and Applications: The DEM Users Manual. Bethesda, Maryland: American Society for Photogrammetry and Remote Sensing 536–539
Sindayihebura A, Meirvenne MV and Nsabimana S (2006) Comparison of Methods for Deriving a Digital Elevation Model from Contours and Modelling of the Associated Uncertainty. Proceedings of Spatial Accuracy, July 5–7 2006, Mario Caetano (ed)
Wilson JP and Gallant JC (2000) Terrain Analysis. Principles and Applications. Wiley, New York, pp. 479
Wise S (2000) Assessing the quality for hydrological applications of digital elevation models derived from contours. Hydrological Processes 14: 1909–1929
Wood J (1996) The Geomorphological Characterization of Digital Elevation Models. Ph.D. Thesis, Department of Geography, University of Leicester, Leicester, UK
Author information
Authors and Affiliations
Corresponding author
About this article
Cite this article
Sharma, A., Tiwari, K.N. & Bhadoria, P.B.S. Measuring the accuracy of contour interpolated digital elevation models. J Indian Soc Remote Sens 37, 139–146 (2009). https://doi.org/10.1007/s12524-009-0005-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12524-009-0005-y