New paper out on using LIDAR to make surface roughness calculations.

Posted: April 11, 2013

Brubaker, K.M., Meyers, W.L., Drohan, P.J., Miller, D.A., and E.W. Boyer. 2013. The use of LIDAR terrain data in characterizing surface roughness and microtopography. Applied and Environmental Soil Science.

The availability of light detection and ranging data (LiDAR) has resulted in a new era of landscape analysis. For example, improvements in LiDAR data resolution may make it possible to accurately model microtopography over a large geographic area; however, data resolution and processing costs versus resulting accuracy may be too costly. We examined two LiDAR datasets of differing resolutions, a low point density (0.714 points/m2 spacing) 1m DEM available statewide in Pennsylvania and a high point density (10.28 points/m2 spacing) 1m DEM research-grade DEM, and compared the calculated roughness between both resulting DEMs using standard deviation of slope, standard deviation of curvature, a pit fill index, and the difference between a smoothed splined surface and the original DEM. These results were then compared to field-surveyed plots and transects of microterrain.Using both data sets, patterns of roughness were identified,which were associated with different landforms derived from hydrogeomorphic features such as stream channels, gullies, and depressions. Lowland areas tended to have the highest roughness values for all methods, with other areas showing distinctive patterns of roughness values across metrics. However, our results suggest that the high-resolution research-grade LiDAR did not improve roughness modeling in comparison to the coarser statewide LiDAR. We conclude that resolution and initial point density may not be as important as the algorithm and methodology used to generate a LiDAR-derived DEM for roughness modeling purposes.