Assessing interpolation accuracy in elevation models

Methods that identify the spatial variation in elevation model accuracy and highlight relative variation are proposed to identify the accuracy preserved in interpolation digital contour data to produce elevation models.

Abstract

Methods that identify the spatial variation in elevation model accuracy and highlight relative variation are proposed. Visualization within the geographic resources analysis support system (GRASS) is used to identify the accuracy preserved in interpolation digital contour data to produce elevation models. The interpolation routines are inverse distance weighting, contour flood filling, simultaneous over-relaxation, and one-dimensional spline fitting. The results of the interpolation process are presented as colored contours, shaded relief maps, aspect maps, and products of Laplacian filtering, profile and plan convexity, and visualizing root mean square error methods.>