Modeling slope uncertainty derived from DEM : a case study in China loess plateau area

Slope is one of a crucial terrain variables in spatial analysis and land use planning, especially in China Loess Plateau area where suffer from serious soil erosion disasters. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived per this method usually does not match with their popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessitous to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in Loess Plateau of China. Six typical geomorphology 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 5m 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 means slope and DEM resolution was found at all test areas, but their regression coefficients related close with the terrain complexity of the test areas. If taking stream channel density to represent terrain, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levers and expressed as (0.0015S2+0.031S-0.0325)·X-0.0045 S2-0.155S+0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new develop methodology applied in this study should be helpful to similar researches in spatial data uncertainty researches.