Share Email Print

Proceedings Paper

Triangulated irregular network (TIN) representation quality as a function of source data resolution and polygon budget constraints
Author(s): Robert F. Richbourg; Tim Stone
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

High resolution digital elevation models (DEM) are becoming increasingly available for use as source data during the process of creating synthetic environments to support simulation systems. Several data sets that provide elevation points corresponding to 1 meter intervals on the earth surface are now available. However, multiple transformations must often be applied to the raw source data before it is suitable for use by any simulation system. These transformations have an impact on the fidelity of the final (simulation) synthetic environment that is difficult to quantify. Further, intuition alone now supports any claim that higher resolution source data necessarily results in generation of higher fidelity simulation data as a product of the transformation process. This paper documents an attempt to measure fidelity differences in final simulation synthetic environments that can be directly attributed to the resolution of the source data. Specifically, several lower resolution DEM are generated from a single high resolution (1 meter horizontal spacing) source DEM and all are used as source data for TIN construction. Automated planning software is applied to each and used as a metric to measure TIN quality.

Paper Details

Date Published: 5 August 1997
PDF: 12 pages
Proc. SPIE 3072, Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision III, (5 August 1997); doi: 10.1117/12.281060
Show Author Affiliations
Robert F. Richbourg, Institute for Defense Analyses (United States)
Tim Stone, Institute for Defense Analyses (United States)

Published in SPIE Proceedings Vol. 3072:
Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision III
David M. McKeown Jr.; J. Chris McGlone; Olivier Jamet, Editor(s)

© SPIE. Terms of Use
Back to Top