HR: 0800h
AN: H41B-0512    [Abstracts]
TI: Estimating sand grain sizes from digital imagery via chord-distribution functions
AU: * Bartlett, M
EM: bartletm@byuh.edu
AF: Brigham Young University - Hawaii, 55-220 Kulanui Street Department of Biochemistry and Physical Sciences Box 1967, Laie, HI 96762, United States
AB: Variations in beach sediment size, supply, and composition are important parameters in understanding patterns of sediment transport and erosion. Traditional methods of characterizing sediments (including mechanical sieving, water column settlement, and laser diffraction) involve recovery of a sample and its removal to the lab for measurement, a time and labor intensive process. Consequently, despite the evidence suggesting the importance of grain size and variability in sediment transport and morphodynamic processes and the inherent spatial and temporal variability of sediments at many locales, most studies are based on relatively few samples. In-situ, rapid characterization of sediments would allow greater spatial data coverage and, consequently, tighter constraints in sediment transport and erosion models. Rubin (J. Sediment. Res., 74, 160-165, 2004) suggested one approach, analyzing the autocorrelation of digital images of sediments to determine grain size distribution rapidly. The technique has the advantages of rapid data collection (via a digital camera) and a relatively straight forward data processing algorithm. However, the autocorrelation technique is not always able to discriminate robustly between different grain morphologies. Using the same tools (digital imagery and computational resources), I examine an alternative approach to characterization of beach sediments: using chord-distribution functions to discriminate grain size distribution and variability. Chord-distribution functions have been shown to be extremely sensitive to small changes in particle morphology in biphasic media (Levitz and Tchoubar, J. Phyisque I, 2, 771-790, 1992). Initial results indicate that with proper pre-processing of the digital image, the technique robustly characterizes the distribution of grains in beach sediment samples from Oahu's north shore.
DE: 3022 Marine sediments: processes and transport
DE: 4217 Coastal processes
DE: 4294 Instruments and techniques
DE: 4558 Sediment transport (1862)
DE: 4594 Instruments and techniques
SC: Hydrology [H]
MN: 2007 Fall Meeting