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Proceedings Paper

Applying dam height-storage curve to geomorphic features analysis within virtual geographic environment: a case study of the Hong-Shi-Mao watershed
Author(s): Daojun Wang; Jianhua Gong; Ainai Ma; Wenhang Li; Xijun Wang
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Paper Abstract

There are generally two kinds of approaches to studying geomorphic features in terms of the quantification level and difference of major considerations. One is the earlier qualitative characterization, and the other is the 2-dimension measurement that includes section pattern and projection pattern. With the development of geo-information technology, especially the 3-D geo-visualization and virtual geographic environments (VGE), 3-dimension measurement and dynamic interactive between users and geo-data/geo-graphics can be developed to understand geomorphic features deeply, and to benefit to the effective applications of such features for geographic projects like dam construction. Storage-elevation curve is very useful for site selection of projects and flood dispatching in water conservancy region, but it is just a tool querying one value from the other one. In fact, storage-elevation curve can represent comprehensively the geomorphic features including vertical section, cross section of the stream and the landform nearby. In this paper, we use quadratic regression equation shaped like y = ax2 + bx + c and the DEM data of Hong-Shi-Mao watershed, Zi Chang County, ShaanXi Province, China to find out the relationship between the coefficients of the equation and the geomorphic features based on VGE platform. It's exciting that the coefficient "a" appear to be correlative strongly with the stream scale, and the coefficient "b" may give an index to the valley shape. In the end, we use a sub-basin named Hao-Jia-Gou of the watershed as an application. The result of correlative research about quadratic regression equation and geomorphic features can save computing and improve the efficiency in silt dam systems planning.

Paper Details

Date Published: 2 December 2005
PDF: 9 pages
Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 604504 (2 December 2005); doi: 10.1117/12.650258
Show Author Affiliations
Daojun Wang, Peking Univ. (China)
Institute of Remote Sensing Applications, Chinese Academy of Sciences (China)
Jianhua Gong, Institute of Remote Sensing Applications, Chinese Academy of Sciences (China)
Ainai Ma, Peking Univ. (China)
Wenhang Li, Institute of Remote Sensing Applications, Chinese Academy of Sciences (China)
Xijun Wang, Yellow River Conservancy Commission (China)


Published in SPIE Proceedings Vol. 6045:
MIPPR 2005: Geospatial Information, Data Mining, and Applications
Jianya Gong; Qing Zhu; Yaolin Liu; Shuliang Wang, Editor(s)

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