Improving a digital elevation model by reducing source data errors and optimising interpolation algorithm parameters: An example in the Loess Plateau, China

Abstract

A hydrologically correct digital elevation model (DEM) forms a basis for realistic environmental modelling, especially in complex terrain. We have performed a study in the Coarse Sandy Hilly Catchments (CSHC) of the Loess Plateau, China, which demonstrates pragmatic, yet effective methods for improving the quality of the DEM by: (1) identifying and correcting source topographic data errors and (2) optimising ANUDEM algorithm parameters. Improvement in the DEM based on fixing over 1100 errors in the input topographic data, and optimising key ANUDEM parameters was assessed using higher accuracy independent validation of 32 contributing areas and 1474 spot heights, and by semi-quantitative analysis of DEM derivatives produced from ANUDEM and Triangular Irregular Network (TIN) algorithms. Improvement in the ANUDEM DEM over the original TIN DEM was shown where the percentage of the total absolute difference in contributing areas reduced from 10.43 to 3.51%, and the bias between the spot heights and DEM elevations reduced from 45 to 32 m. Large improvement in DEM quality was gained by using ANUDEM instead of TIN, with smaller improvement gained by fixing source data errors, and optimising ANUDEM parameters. Show more