Share Email Print

Proceedings Paper

The digital generalization principle of digital elevation model
Author(s): Hai Hu; Jun Gao; Peng Hu
Format Member Price Non-Member Price
PDF $14.40 $18.00
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

This paper briefly is based on the discussion of three fundamental characteristics of the ground (elevation accuracy, validity of elevation order, and the preservation of elevation features) and the concept of the model, then analyses major theoretical and practical shortcomings of the DEM generated in the mechanical model in depth, finally we proposes and discusses objects for feature modeling and the way of digital generalization, and discusses the principle of DEM digital generalization. We also give the 1:5 0000 and 1:1 0000 two series of DEM generalization maps, which achieve the desired results. Experimental results clearly show that: Only with digital generalization based on reliable DEMs which have expressed all terrain features, we can express DEM of required terrain feature on designated resolutions. That is no generalizing, there will be no DEM. The excellent consistency of Theoretical analysis and experimental results, makes this paper believe that objects for feature modeling and digital generalization will bring qualitative change to DEM, and will be a promising new way to solve hundred-year problem -combination and generalization of contours and water portfolio.

Paper Details

Date Published: 16 October 2009
PDF: 8 pages
Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 749221 (16 October 2009); doi: 10.1117/12.838546
Show Author Affiliations
Hai Hu, Wuhan Univ. (China)
Jun Gao, Zhengzhou Institute of Geodesy and Geomatics (China)
Peng Hu, Wuhan Univ. (China)

Published in SPIE Proceedings Vol. 7492:
International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining
Yaolin Liu; Xinming Tang, Editor(s)

© SPIE. Terms of Use
Back to Top