Reduction of errors in digital terrain parameters used in soil - landscape modelling

Quality of digital elevation models (DEMs) and DEM-derived products directly affects the quality of terrain analysis applications. The objective of this work was to review and systematise methods to improve geomorphic plausibility of DEMs and minimise artefacts and outliers in terrain parameters. Three approaches to the reduction of errors in DEM and DEM-derived products are described: (a) by using empirical knowledge, e.g. to adjust elevations using medial axes or stream networks; (b) by applying filtering operations and (c) by averaging terrain parameters derived from multiple realisations of DEM, i.e. using error propagation technique. The methods were tested using a 3.8×3.8 km sample area covering two distinct landscapes: hilland and plain with terraces. The DEM was produced by linear interpolation of contour data. The proportion of artefacts (padi terraces) in the unfiltered DEM was 17.3%. After the addition of medial axes, filtering of outliers and adjustment of elevation for streams, the proportion of padi terraces was reduced to 2.2%. Remaining errors in terrain parameters such as undefined pixels and local outliers were reduced using repeated filtering (with iterations). All terrain parameters were also calculated by averaging multiple realisations. Both the filtering approach and averaging multiple realisations give somewhat smoother maps of terrain parameters. The advantage of filtering of outliers is that it employs the spatial autocorrelation structure. The advantage of averaging multiple realisations is that it can be easier automated. The reduction of errors improved the mapping of landform facets (classification) and solum thickness (regression). The classification accuracy increased from 51.3 to 72% and the R2 of the regression model for the prediction of the solum thickness increased from 0.27 to 0.40. These methods can be used to filter DEMs derived from contour data and terrain parameters, but also to reduce errors in other types of gridded DEMs and DEM-derived products.