Augmenting grid-based contours to improve thin plate dem generation. Photogrammetric Engine.pdf
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Augmenting grid-based contours to improve thin plate dem generation. Photogrammetric Engine
Augmenting Grid-based Contours to Improve Thin
Plate DEM Generation
April 4, 2003
Michael B. Gousie
Department of Mathematics Computer Science
Wheaton College
Norton, MA 02766
Wm. Randolph Franklin
Electrical, Computer, and Systems Engineering Department
Rensselaer Polytechnic Institute
Troy, NY 12180
Abstract
We present two new pre-processing techniques that improve thin plate Digital El-
evation Model (DEM) approximations from grid-based contour data. One method
computes gradients from an initial interpolated or approximated surface. The aspects
are used to create gradient lines that are interpolated using Catmull-Rom splines. The
computed elevations are added to the initial contour data set. Thin plate methods
are applied to all of the data. The splines allow information to flow across contours,
improving the final surface. The second method successively computes new, interme-
diate contours in between existing isolines, which provide additional data for subse-
quent thin plate processing. Both methods alleviate artifacts visible in previous thin
plate methods. The surfaces are tested with published methods to show qualitative and
quantitative improvements over previous methods.
2
1 Introduction
Geographical Information Systems (GIS) are becoming increasingly popular for visual-
izing spatial data. Most systems layer patterns or colors, which depict data such as soil
type, roads, and the like, over a two-dimensional map. As technology continues to im-
prove, users increasingly expect to view such data in three-dimensions, as is now done
in ArcView and MapInfo. The user can then view the desired data in the context of the
surrounding topology.
Digital Elevation Models (DEM) are often used to store three-dimensional elevation
data via a regular grid. Because DEMs are not available for many areas and/or because
they are storage intensive, they are often interpolated or approximated from sparse data.
We have chosen isoline data from which to compute DEMs because con
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