Paper
29 December 2008 Spatial interpolation of DEM using BP artificial neural networks
Shuwei Wang, Fei Li
Author Affiliations +
Proceedings Volume 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA); 728534 (2008) https://doi.org/10.1117/12.815431
Event: International Conference on Earth Observation Data Processing and Analysis, 2008, Wuhan, China
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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shuwei Wang and Fei Li "Spatial interpolation of DEM using BP artificial neural networks", Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728534 (29 December 2008); https://doi.org/10.1117/12.815431
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Cited by 2 scholarly publications.
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KEYWORDS
Artificial neural networks

Lithium

Error analysis

Neurons

Algorithm development

Geographic information systems

Neural networks

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