Effects of Terrain Morphology, Sampling Density, and Interpolation Methods on Grid DEM Accuracy

This paper explores the effects of terrain morphology, sampling density, and interpolation methods for scattered sample data on the accuracy of interpolated heights in grid Digital Elevation Models (DEM). Sampled data were collected with a 2 by 2 meters sampling interval from seven different morphologies, applying digital photogrammetric methods to large scale aerial stereo imagery (1:5000). The experimen- tal design was outlined using a factorial scheme, and an analysis of variance was carried out. This analysis yielded the following main conclusions: DEM accuracy (RMSE) is affected significantly by the variables studied in this paper according to "morphologysampling densityinterpola- tion" method. Multiquadric Radial Basis Function (RBF) was rated as the best interpolation method, although Multilog RBF performed similarly for most morphologies. The rest of RBF interpolants tested (Natural Cubic Splines, Inverse Multiquadric, and Thin Plate Splines) showed numerical instability working with low smoothing factors. Inverse Distance Weighted interpolant performed worse than RBF Multiquadric or RBF Multilog. In addition, it is found that the relationship between the RMSE and the sampling density N is adjusted to a decreasing potential function that may be expressed as RMSE/Sdz � 0.1906(N/M) � 0.5684 (R 2 � 0.8578), being Sdz the standard deviation of the heights of the M check points used for accuracy estimation, and N the number of sampling points used for creating the DEM. The results obtained in this study allow us to observe the possibility of establishing empirical relationships between the RMSE expected in the interpolation of a Grid DEM and such variables as terrain ruggedness, sampling density, and the interpolation method, among others that could be added. Therefore, it would be possible to establish a priori the optimum grid size required to generate or storage a DEM of a particular accuracy, with the economy in computing time and file size that this would signify for the digital flow of the mapping information.

[1]  J. Royston Expected Normal Order Statistics (Exact and Approximate) , 1982 .

[2]  G. Gilat,et al.  Method for smooth approximation of data , 1977 .

[3]  E. Baltsavias,et al.  Integration of image analysis and GIS , 1999 .

[4]  H. MITAOVA,et al.  General Variational Approach to the Interpolation Problem , 1988 .

[5]  M. Goodchild,et al.  The Fractal Nature of Geographic Phenomena , 1987 .

[6]  Joseph. Wood,et al.  The geomorphological characterisation of Digital Elevation Models , 1996 .

[7]  Shmuel Rippa,et al.  An algorithm for selecting a good value for the parameter c in radial basis function interpolation , 1999, Adv. Comput. Math..

[8]  N. Lam Spatial Interpolation Methods: A Review , 1983 .

[9]  Zhilin Li,et al.  ON THE MEASURE OF DIGITAL TERRAIN MODEL ACCURACY , 2006 .

[10]  R. Franke Scattered data interpolation: tests of some methods , 1982 .

[11]  P. Burrough,et al.  Principles of geographical information systems , 1998 .

[12]  Jay Gao,et al.  Resolution and Accuracy of Terrain Representation by Grid DEMs at a Micro-Scale , 1997, Int. J. Geogr. Inf. Sci..

[13]  Fernando José Aguilar Torres,et al.  Evaluación de diferentes técnicas de interpolación espacial para la generación de modelos digitales de elevación del terreno agrícola , 2001 .

[14]  R. E. Carlson,et al.  The parameter R2 in multiquadric interpolation , 1991 .

[15]  L. Montefusco,et al.  Radial basis functions for the multivariate interpolation of large scattered data sets , 2002 .

[16]  C. Helpke,et al.  State-of-the-art of digital photogrammetric workstations for topographic applications , 1995 .

[17]  Michel Kasser,et al.  Generation of digital terrain and surface models , 2001 .

[18]  D. Weber,et al.  Evaluation and comparison of spatial interpolators II , 1992 .

[19]  Zhilin Li,et al.  Effects of check points on the reliability of DTM accuracy estimates obtained from experimental tests , 1991 .

[20]  Richard F. Keim,et al.  Digital terrain modeling of small stream channels with a total-station theodolite , 1999 .

[21]  B. Makarovic,et al.  Structures for geo-information and their application in selective sampling for digital terrain models , 1984 .

[22]  J. Poesen,et al.  Importance of slope gradient and contributing area for optimal prediction of the initiation and trajectory of ephemeral gullies , 1999 .

[23]  Qihao Weng Quantifying Uncertainty of Digital Elevation Models Derived from Topographic Maps , 2002 .

[24]  Jichun Li,et al.  A simple efficient algorithm for interpolation between different grids in both 2D and 3D , 2002, Math. Comput. Simul..

[25]  Xiaojun Yang,et al.  Visual and Statistical Comparisons of Surface Modeling Techniques for Point-based Environmental Data , 2000 .

[26]  Franky Albert Noël Declercq,et al.  Interpolation Methods for Scattered Sample Data: Accuracy, Spatial Patterns, Processing Time , 1996 .

[27]  Dennis Weber,et al.  Evaluation and comparison of spatial interpolators , 1992 .

[28]  Z. Yu Surface interpolation from irregularly distributed points using surface splines, with Fortran program , 2001 .

[29]  W. Hargrove,et al.  Photogrammetric Engineering & Remote Sensing , 2022 .

[30]  Lucien Wald,et al.  Joint EARSeL/ISPRS Workshop "fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects". Valladolid, Spain, 3-4 June 1999. International Archives of Photogrammetry and Remote Sensing, vol. 32, Part 7-4-3W6 , 1999 .

[31]  Marc Voltz,et al.  A comparison of kriging, cubic splines and classification for predicting soil properties from sample information , 1990 .

[32]  R. L. Hardy Multiquadric equations of topography and other irregular surfaces , 1971 .

[33]  Peter F. Fisher,et al.  Assessing interpolation accuracy in elevation models , 1993, IEEE Computer Graphics and Applications.

[34]  H. Mitásová,et al.  General variational approach to the interpolation problem , 1988 .

[35]  H. Mitásová,et al.  Interpolation by regularized spline with tension: I. Theory and implementation , 1993 .

[36]  Zhilin Li VARIATION OF THE ACCURACY OF DIGITAL TERRAIN MODELS WITH SAMPLING INTERVAL , 2006 .

[37]  Wm. Randolph Franklin Applications of Analytical Cartography , 2000 .

[38]  Curt H. Davis,et al.  HIGH-RESOLUTION DEMS FOR URBAN APPLICATIONS FROM NAPP PHOTOGRAPHY , 2001 .

[39]  S. Robeson Spherical Methods for Spatial Interpolation: Review and Evaluation , 1997 .

[40]  Jaroslav Hofierka,et al.  Interpolation by regularized spline with tension: II. Application to terrain modeling and surface geometry analysis , 1993 .

[41]  Thierry Toutin,et al.  Impact of terrain slope and aspect on radargrammetric DEM accuracy , 2002 .