Articles | Volume 10, issue 3
The Cryosphere, 10, 1039–1054, 2016

Special issue: Intercomparison of methods to characterise snow...

The Cryosphere, 10, 1039–1054, 2016

Research article 19 May 2016

Research article | 19 May 2016

Sensitivity of snow density and specific surface area measured by microtomography to different image processing algorithms

Pascal Hagenmuller1,2, Margret Matzl3, Guillaume Chambon2, and Martin Schneebeli3 Pascal Hagenmuller et al.
  • 1Météo-France – CNRS, CNRM-GAME, UMR3589, CEN, 1441 rue de la piscine, 38400 Saint Martin d'Hères, France
  • 2Université Grenoble Alpes, Irstea, UR ETGR, 2 rue de la Papeterie – BP 76, 38402 Saint Martin d'Hères, France
  • 3WSL Institute for Snow and Avalanche Research SLF, Fluelastrasse 11, 7260 Davos Dorf, Switzerland

Abstract. Microtomography can measure the X-ray attenuation coefficient in a 3-D volume of snow with a spatial resolution of a few microns. In order to extract quantitative characteristics of the microstructure, such as the specific surface area (SSA), from these data, the greyscale image first needs to be segmented into a binary image of ice and air. Different numerical algorithms can then be used to compute the surface area of the binary image. In this paper, we report on the effect of commonly used segmentation and surface area computation techniques on the evaluation of density and specific surface area. The evaluation is based on a set of 38 X-ray tomographies of different snow samples without impregnation, scanned with an effective voxel size of 10 and 18 μm. We found that different surface area computation methods can induce relative variations up to 5 % in the density and SSA values. Regarding segmentation, similar results were obtained by sequential and energy-based approaches, provided the associated parameters were correctly chosen. The voxel size also appears to affect the values of density and SSA, but because images with the higher resolution also show the higher noise level, it was not possible to draw a definitive conclusion on this effect of resolution.

Short summary
The paper focuses on the characterization of snow microstructure with X-ray microtomography, a technique that is progressively becoming the standard for snow characterization. In particular, it rigorously investigates how the image processing algorithms affect the subsequent microstructure characterization in terms of density and specific surface area. From this analysis, practical recommendations concerning the processing X-ray tomographic images of snow are provided.