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Abstract |
This paper examines the effect of scale (exhibited by spatial sampling) in modeling mean slope from lidar data using two representations of scale: lidar posting density (i.e. post‐spacing) and DEM resolution (i.e. cell size). The study areas selected include six small (i.e. approximately 3 km2) urban drainage basins in Richland County, SC, USA, which share similar hydrologic characteristics. This research spatially sampled an airborne lidar dataset collected in 2000 at a 2 m nominal posting density to simulate lidar posting density at various post‐spacings, from 2 m through 10 m. DEMs were created from the lidar observations at a corresponding cell size using spatial interpolation. Finally, using these DEMs, a sensitivity analysis between modeled terrain slope and lidar post‐spacing was conducted. Results of the sensitivity analyses showed that the deviation between mean slope and modeled mean slope decreases with finer posting density and DEM resolution. The relationship of mean slope with varying cell sizes and post‐spacing suggests a linear and a logarithmic function, respectively, for all study areas. More importantly, cell size has a greater effect on mean slope than lidar posting density. Implications of these results for lumped hydrologic modeling are then postulated. |
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