Granulometric characterization of paleosols in loess series by automated static image analysis

Abstract

An automated image analysis method is proposed here to study the size and shape of siliciclastic sedimentary particles of paleosols of Central European loess sequences. Several direct and indirect measurement techniques are available for grain size measurements of sedimentary mineral particles. Indirect techniques involve the use of some kind of physical laws, however, all requirements for calculations are in many cases not known. Even so, the direct manual microscopic observation and measurement of large, representative number of grains is timeconsuming and sometimes rather subjective. Therefore, automated image analyses techniques provide a new and perspective way to analyse grain size and shape sedimentary particles. Here we test these indirect and direct techniques and provide new granulometric data of paleosols. Our results demonstrate that grain size data of the mineral dust samples are strongly dependent on shape parameters of particles, and shape heterogeneity was different of the different size classes. Due to the irregular grain shape parameters, uncertainties have arisen also for the sizes. In this paper we present a possible correction procedure to reduce the differences among the results of the laser diffraction and image analysis methods. By applying new correction factors, results of the two approaches could be get closer but the most definite factor, the unknown thickness of particles remained a problem to solve. The other presented method to assess the uncertain 3 rd dimension of particles by their intensity-size relationships makes us able to reduce further the deviations of the two sizing methods.

Plio-Pleistocene Dust Traps on Paleokarst Surfaces: A Case Study From the Carpathian Basin

“…In this study, values of 1.54 for the refractive index and 0.1 for the absorption coefficient (1.54-i0.1) were applied, while 1.33 for the refractive index was used for the dispersant water. Reported refractive indices of soil-forming minerals generally fall within a relatively narrow range, in overlap with the value adopted in this study (Varga et al, 2018(Varga et al, , 2019. However, the exact value of the absorption coefficient is also dependent on particle shape and surface roughness beside the mineralogical composition (Varga et al, 2018(Varga et al, , 2019.…”

“…Reported refractive indices of soil-forming minerals generally fall within a relatively narrow range, in overlap with the value adopted in this study (Varga et al, 2018(Varga et al, , 2019. However, the exact value of the absorption coefficient is also dependent on particle shape and surface roughness beside the mineralogical composition (Varga et al, 2018(Varga et al, , 2019. As stated by Varga et al (2019), "to get an overview on the effects of optical settings on particle size distributions, sensitivity tests were made with the combination of various refractive indices (Ri: 1.45-1.6) and absorption coefficients (Ac: 0.01-1).…”

“…Grain-size of the samples was made using a Malvern Mastersizer 3000 laser scattering device. With the wet dispersion unit (Hydro LV), particle size distributions are given as volume percentage of particles classed into 101 logarithmically distributed (log-spaced) size bins from 0.01 to 2,100 µm (Varga et al, 2018(Varga et al, , 2019. Laser light scattering features of this instrument are discussed in detail in Varga et al (2018Varga et al ( , 2019.…”

“…With the wet dispersion unit (Hydro LV), particle size distributions are given as volume percentage of particles classed into 101 logarithmically distributed (log-spaced) size bins from 0.01 to 2,100 µm (Varga et al, 2018(Varga et al, , 2019. Laser light scattering features of this instrument are discussed in detail in Varga et al (2018Varga et al ( , 2019. In this study, values of 1.54 for the refractive index and 0.1 for the absorption coefficient (1.54-i0.1) were applied, while 1.33 for the refractive index was used for the dispersant water.…”

Comparison and quantitative analysis of microstructure parameters between original loess and remoulded loess under different wetting-drying cycles

“…Then, the following parameters were divided to three types: size (the average diameter d), shape (the ratio of short diameter to long diameter C, circularity R, the average shape factor F, and morphological fractal dimension D) and arrangement (Directional frequency F(α), anisotropy rate I n , directional probability entropy H m , and directional fractal dimension D f ). All these parameters were chosen as the microstructural parameters of the sample loess particles 19,20 . The parameters were calculated as follows: www.nature.com/scientificreports www.nature.com/scientificreports/ The average diameter d is the diameter of the equivalent circle, whose area is equal to the area of the loess particle so that the size of the particle can be described by Eq.…”