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Mapping Quaternary alluvial fans in the southwestern United States based on multiparameter surface roughness of lidar topographic data
Author(s) -
Regmi Netra R.,
McDonald Eric V.,
Bacon Steven N.
Publication year - 2014
Publication title -
journal of geophysical research: earth surface
Language(s) - English
Resource type - Journals
eISSN - 2169-9011
pISSN - 2169-9003
DOI - 10.1002/2012jf002711
Subject(s) - geology , alluvial fan , alluvium , surface roughness , curvature , landform , geomorphology , surface finish , scale (ratio) , lidar , geometry , remote sensing , cartography , geography , mathematics , materials science , structural basin , composite material
Quaternary alluvial fans have diverse surface morphologies related to both depositional and weathering processes. Numerous studies have demonstrated that the surface expression and morphometry of alluvial fans can be used as an indicator of their relative age of deposition, but only recently has there been an effort to utilize high‐resolution topographic data to differentiate alluvial fans by surface age with automated and quantifiable routines. We developed a quantitative model for mapping the relative age of alluvial fan surfaces based on multiparameter surface roughness values computed from 1 m resolution lidar topographic data. Roughness is defined as a function of observational scale and integration of slope, curvature, and aspect topographic parameters. Alluvial fan roughness values were computed across multiple observation scales (3 × 3 m to 150 × 150 m) based on the standard deviation (SD) of slope, curvature (tangential), and aspect topographic parameters. Plots of roughness value versus size of observation scale suggest that the SD of each parameter over a 7 × 7 m observation window best identified the signature of surface roughness elements. Roughness maps derived from slope, curvature, and aspect at this scale were integrated using fuzzy logic. The integrated roughness map was then classified into five relative morphostratigraphic surface age categories (active wash to ~400 ka) and statistically compared with a similar fivefold surface age map of alluvial fans developed using traditional field surveys and aerial photographic interpretation. The model correctly predicted the distribution and relative surface age of ~61% of alluvial fan landforms based on traditional mapping techniques.