The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a cooperative effort between NASA and Japan's Ministry of Economy Trade and Industry (METI), with the collaboration of scientific and industry organizations in both countries. The ASTER instrument provides a more robust remote sensing imaging capability when compared to the older Landsat Thematic Mapper. This paper deals with the accuracy assessment of elevation data obtained using ASTER from each of the eleven (11) selected extrapolation/interpolation algorithms: Inverse Distance Weighting, Natural Neighbor, Spline Regular, Spline Tension, Universal Kriging, Empirical Bayesian Kriging, Topo to Raster, global (trend surface), local polynomial, kernel interpolation with barriers and radial basis functions in Digital Elevation Model (DEM) surface creation. The data were compared with reference to ground control points of differential GPS measurements in the study area. The error statistics were generated between DGPS measurements and Extracted elevation data from each selected interpolation method. It was observed that Spline Regular Interpolation shown the best overall accuracy of ±11.520m when elevation data extracted from Inverse distance weighting, Natural Neighbour, Spline T, Topo to Raster, Universal Kriging, Empirical Bayesian kriging, Global polynomial interpolation (GPI), local polynomial interpolation (LPI), Radial basis function and Kernel interpolation of ±15.170, ±14.340, ±12.336, ±13.551, ±14.707, ±13.711, ±15.363, ±13.964, ±13.590 and ±15.376 respectively when compared with elevation values from GPS method. The study recommends capacity building in the form of workshop, training, and flexible integration of point elevation data to DEM.
P. A. Burrough, P. F. Van Gaans, J. Wilson and A. J Hansen, GIS and Geostatistics: Essential Partners for Spatial Analysis, 2001.
C. A. Felgueiras, E. C. Camargo, and J. Ortiz, Exploring Geostatistical Methods to Improve the Altimetry Accuracies of Digital Elevation Models, 2015.
T. Hengl, B. Bajat, D. Blagojevic, H. I. Reuter, Geostatistical modeling of topography using auxiliary maps. Computers & Geosciences, p. 1886-1899, 2008.
N.S.N, Lam, Spatial Interpolation Methods: A Review. The American Cartographer, Vol. 10, No. 2, 129-149, 1983.
R.R. Rodriguez, Integration of Topographic and Bathymetric Digital Elevation Model using ArcGIS Interpolation Methods: A Case Study of the Klamath River Estuary, 2015.
J. M. Stoker, H. K Heidemann, G. A. Evans and S. K Greenlee., “A conceptual prototype for the next-generation national elevation dataset”. Open-File report2013-1023, U.S. Geological Survey, 2013.
This work is licensed under a Creative Commons Attribution 4.0 International License.
The names and email addresses entered in this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party.
Submission of the manuscript represents that the manuscript has not been published previously and is not considered for publication elsewhere.