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Proceedings Paper

Analysis on slope uncertainty based on different resolution level DEM: a case study
Author(s): Wenfu Peng; Jieming Zhou; Cun-jian Yang; Zhengwei He
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Paper Abstract

Digital Elevation Model (DEM) is indispensable for much analysis such as topographic feature extraction, runoff analysis, slope stability analysis, landscape analysis and so on. Such analysis requires a high accurate DEM. The accuracy of DEM is usually represented by spatial resolution and height accuracy. Slope is one of the crucial terrain variables in spatial analysis and land use planning, especially in the mountain region which is suffering from serious soil erosion. However slope accuracy derived from DEM usually does not match with its popularity. A quantitative simulation to slope uncertainty is important not only theoretically but also necessarily to applications. The objective of this study was to analyze the slope uncertainty of Yizi following GIS based on different DEM resolution. Comparative and math-simulation methodology was employed for data processing and analysis. There is a linear correlativity between mean slope, slope change rate and different DEM resolution within the study area, and the analysis and simulation result shows that different DEM resolution has great influence on slope uncertainty. This methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation.

Paper Details

Date Published: 10 November 2008
PDF: 12 pages
Proc. SPIE 7146, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses, 71460W (10 November 2008); doi: 10.1117/12.813123
Show Author Affiliations
Wenfu Peng, Chengdu Univ. of Technology (China)
Sichuan Normal Univ. (China)
Jieming Zhou, Sichuan Normal Univ. (China)
Cun-jian Yang, Chengdu Univ. of Technology (China)
Zhengwei He, Chengdu Univ. of Technology (China)


Published in SPIE Proceedings Vol. 7146:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang, Editor(s)

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