A rapid method of measuring snow-surface profiles
Quantitative data on the surface profile of a snowpack are required for a number of applications, including detailed hydrological modelling and modelling the interaction of electromagnetic radiation with the surface. The availability of low-cost digital cameras allows these to be obtained with subst...
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Veröffentlicht in: | Journal of glaciology 1998, Vol.44 (148), p.674-675 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Quantitative data on the surface profile of a snowpack are required for a number of applications, including detailed hydrological modelling and modelling the interaction of electromagnetic radiation with the surface. The availability of low-cost digital cameras allows these to be obtained with substantial savings in time. Data were acquired during a short field trip to Scotland in mid-March 1998, as part of a project to validate synthetic-aperture radar observations of wet snow. At a number of test sites, a portable back plate (constructed from 1 mm gauge aluminium sheet, 1 m long and 20 cm wide, hinged so it could fold to 50 cm x 20 cm, and painted matte black) was inserted vertically into the snow and photographed using a pocket-sized digital camera that recorded images as arrays of 640 x 480 pixels. To obtain surface roughness data, images must be processed to generate a set of (x, y) coordinates corresponding to the snow edge. The image-processing operations that are required are not complicated and can be performed by a large number of image-processing programs. The following analysis was performed on a Macintosh computer using the public domain NIH Image program, developed at the U.S. National Institutes of Health and available on the internet at http:/ /rsb.info.nih.gov/nih-image/. Two major advantages of this program are its comparatively small size and the fact that it has a macro programming language that allows the user to define reasonably complex processing algorithms and to export numerical data. The algorithm adopted here involves the following steps: 1. Thresholding, followed by conversion to a binary image. 2. Edge detection. 3. Skeletonization. 4. Digitizing. Each of these steps is discussed below. |
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ISSN: | 0022-1430 1727-5652 |
DOI: | 10.1017/S0022143000002197 |