Some examples include measuring small-scale seafloor bottom roughness from microtopographic laser scanning (Du Preez and Tunnicliffe 2012),[3] and deriving multi-scale measures of rugosity, slope and aspect from benthic stereo image reconstructions (Friedman et al.
[4] Despite the popularity of using rugosity for two- and three-dimensional surface analyses, methodological inconsistency has been problematic.
[5] The ACR rugosity index is defined as the contoured (real) surface area divided by the area of the surface orthogonally projected onto a plane of best fit (POBF), where the POBF is a function (linear interpolation) of the boundary data only.
Geology: For marine geologists and geomorphologists, rugosity is a useful characteristic in distinguishing different types of seafloors in remote sensing applications (e.g., sonar and laser altimetry, based from ships, planes or satellites).
Oceanography: Among oceanographers, rugosity is recognized to influence small-scale hydrodynamics by converting organized laminar or oscillatory flow into energy-dissipating turbulence.