Carlos Henrique Grohmann

Surface roughness is an important geomorphological variable which has been used in the earth and planetary sciences to infer material properties, current/past processes and the time elapsed since formation. No single definition exists, however within the context of geomorphometry we use surface roughness as a expression of the variability of a topographic surface at a given scale, where the scale of analysis is determined by the size of the landforms or geomorphic features of interest. Six techniques for the calculation of surface roughness were selected for an assessment of the parameters behaviour at different spatial scales and dataset resolutions. Area ratio operated independently of scale, providing consistent results across spatial resolutions. Vector dispersion produced results with increasing roughness and homogenisation of terrain at coarser resolutions and larger window sizes. Standard deviation of residual topography tends to highlight local features and doesnt detect regional relief. Standard deviation of elevation correctly identified breaks-of-slope and was good at detecting regional relief. Standard deviation of slope (SDslope) also correctly identified smooth sloping areas and breaks-of-slope, providing the best results for geomorphological analysis. Standard deviation of profile curvature identified the breaks-of-slope, although not as strongly as SDslope and it is very sensitive to noise and spurious data. In general, SDslope offered good performance at a variety of scales, whilst the simplicity of calculation is perhaps its single greatest benefit.