Error in a USGS 30-meter digital elevation model and its impact on terrain modeling

Calculations based on US Geological Survey (USGS) digital elevation models (DEMs) inherit any errors associated with that particular representation of topography. We investigated the potential impact of error in a USGS 30 m DEM on terrain analysis over 27 km2. The difference in elevation between 2652 differential Global Positioning Systems measurements and USGS 30-m DEM derived elevations provided the comparative error dataset. Analysis of this comparative error data suggested that although the global (average) error is small, local error values can be large, and also spatially correlated. Stochastic conditional simulation was used to generate multiple realizations of the DEM error surface that reproduce the error measurements at their original locations and sample statistics such as the histogram and semivariogram model. The differences between these alternative error surfaces provide a model of uncertainty for the unknown DEM error spatial distribution. These DEM errors had a significant impact on terrain attributes which compound elevation values of many grid cells (e.g. slope, wetness index, etc.). A case study using terrain modeling demonstrates that the result of error propagation is most dramatic in valley bottoms and along streamlines.