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The effect of cell resolution on depressions in Digital Elevation Models

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Version 2 2016-10-14, 05:17
Version 1 2016-10-14, 05:15
journal contribution
posted on 2016-10-14, 05:17 authored by Zandbergen, Paul A
A proper understanding of the occurrence of depressions is necessary to understand how they affect the processing of a Digital Elevation Model (DEM) for hydrological analysis. While the effect of DEM cell resolution on common terrain derivatives has been well established, this is not well understood for depressions. The more widespread availability of high resolution DEMs derived through Light Detection and Ranging (LIDAR) technologies presents new challenges and opportunities for the characterization of depressions. A 6-meter LIDAR DEM for a study watershed in North Carolina was used to determine the effect of DEM cell resolution on the occurrence of depressions. The number of depressions was found to increase with smaller cell sizes, following an inverse power relationship. Scale-dependency was also found for the average depression surface area, average depression volume, total depression area and total depression volume. Results indicate that for this study area the amount of depressions in terms of surface area and volume is at a minimum for cell sizes around 30 to 61 meters. In this resolution range there will still be many artificial depressions, but their presence is less than at lower or higher resolutions. At finer scales, the (small) vertical error of the LIDAR DEM needs to be considered and introduces a large number of small and shallow artificial depressions. At coarser scales, the terrain variability is no longer reliably represented and a substantial number of large and sometimes deep artificial depressions is created. The results presented here support the conclusion that the use of the highest resolution and most accurate data, such as LIDAR-derived DEMs, may not result in the most reliable estimates of terrain derrivatives unless proper consideration is given to the scale-dependency of the parameters being studied.

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