Abstract
The accuracy of digital elevation models (DEM) and DEM-derived products depends on several factors, including the horizontal resolution and vertical precision at which the elevation data are represented, and the source of the elevation data. This accuracy becomes increasingly important as we extend the use of DEM data for spatial prediction of soil attributes. Our objective was to compare terrain attributes and quantitative soil-landscape models derived from grid-based DEM represented at different horizontal resolutions (10 and 30 m), represented at different vertical precisions (0.1 and 1 m), and acquired from different sources. Decreasing the horizontal resolution of the field survey DEM produced lower slope gradients on steeper slopes, steeper slope gradients on flatter slopes, narrower ranges in curvatures, larger specific catchment areas in upper landscape positions, and lower specific catchment areas values in lower landscape positions. Overall, certain landscape features were less discernible on the 30-m DEM than on the 10-m DEM. Decreased vertical precision produced a large proportion of points with zero slope gradient and zero slope curvature, and a large number of steeply sloping and more highly curved areas. Differences among DEM from different sources were more significant, with less accurate representation of depressions and drainage pathways with the USGS DEM as compared to the field survey DEM. Empirical models developed from different DEM included similar predictive terrain attributes, and were equally successful in predicting A-horizon depth (AHD) in the validation data set.
Original language | English (US) |
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Pages (from-to) | 67-89 |
Number of pages | 23 |
Journal | Geoderma |
Volume | 100 |
Issue number | 1-2 |
DOIs | |
State | Published - 2001 |
Bibliographical note
Funding Information:Portions of this research were supported by funds provided by the United States Department of Agriculture Natural Resources Conservation Service, the United States Corps of Engineers Waterways Experiment Station, the Minnesota Agricultural Experiment Station, and the University of Minnesota Graduate School. We also thank Dr. John Grove, Dr. John Kabrick, and Dr. Ed Perfect for offering many thoughtful comments that improved this manuscript.
Keywords
- Digital elevation model
- Resolution
- Soil-landscape
- Spatial model
- Spatial variability
- Terrain analysis