Acta Geographica Sinica ›› 2003, Vol. 58 ›› Issue (6): 824-830.doi: 10.11821/xb200306004

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Modeling Slope Uncertainty Derived from DEMs in Loess Plateau

TANG Guoan1,2, ZHAO Mudan1,3, LI Tianwen1, LIU Yongmei1,3, XIE Yuanli1   

  1. 1. Department of Urban and Resource Science, Northwest University, Xi'an 710069, China;
    2. The Key Open Laboratory of Continental Dynamics, Ministry of Education, Northwest University, Xi'an 710069, China;
    3. Institute of Soil and Water Conservation, CAS and Ministry of Water Resources, Yangling 712100, China
  • Received:2003-07-19 Revised:2003-09-03 Online:2003-11-25 Published:2003-11-25
  • Supported by:

    National Nature Science Foundation of China, No.40271089; National High Technique Research Development Project, No.2001AA130023; Senior Visiting Scholar Project of National Laboratory for Information Engineering in Survey, Mapping and Remote Sensing


Slope is one of crucial terrain variables in spatial analysis and land use planning, especially in the Loess Plateau area of China where rugged terrains enhance serious soil erosion. DEM based on slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with their popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10000 scale topographical maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in loess area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas, but their regression coefficients were closely related with the terrain complexity of the test areas. If stream channel density was taken to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels could be expressed as (0.0015S2 + 0.031S - 0.0325)X - 0.0045S2 - 0.155S + 0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications.

Key words: Loess Plateau, DEM, slope, resolution, uncertainty