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Proceedings Paper

Spatial interpolation of DEM using BP artificial neural networks
Author(s): Shuwei Wang; Fei Li
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Paper Abstract

In this paper, we specially emphasize on BP Artificial Neural Networks (BP ANNs) in spatial interpolation of DEM, and simulate one spatial interpolation case in the area where there are several discrete known levelling points using input vector: (X, Y, XY, X2, Y2) or (X, Y, XY, X2, Y2, XY2, X2Y, X3, Y3)instead of (X,Y), where the X is the horizontal coordinate and the Y is the vertical coordinate. The results show that the new input vectors are usually applicable and better than the classic one. In the numerical experiment of this paper, the maximum error is 2.032m when the input vector, (X, Y, XY, X2, Y2, XY2, X2Y, X3, Y3) is used, while it is 2.807m when (X, Y) is applied. Further this BP ANNs method is better than the classic polynomial method in which the maximum error of polynomial method is 6.728m.

Paper Details

Date Published: 29 December 2008
PDF: 8 pages
Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728534 (29 December 2008); doi: 10.1117/12.815431
Show Author Affiliations
Shuwei Wang, Wuhan Univ. (China)
Fei Li, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 7285:
International Conference on Earth Observation Data Processing and Analysis (ICEODPA)
Deren Li; Jianya Gong; Huayi Wu, Editor(s)

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