Observing Microscale Variations in Snow Stratigraphy Using Near Infra-red Photography
Abstract
The physical characteristics of snowpacks in arctic tundra can be highly spatially heterogeneous. Consequently, understanding the small scale (sub-metre) variability can provide valuable information for evaluating remotely sensed images that integrate snowpack variability over much greater spatial scales. Here we outline a new method, developing on work by Matzl and Schneebeli (2006), to quickly obtain in-situ observations of centimetre resolution snowpack stratigraphy along 10 m trenches. Mie theory suggests that the reflectance of snow in the near infra-red (NIR) spectrum is largely controlled by grain size. This reflectance is not unduly influenced by impurities in the snow or variations in density, so long as densities are less than 650 kg/m3. Consequently, stratigraphic boundaries where grain size differs can be defined by the reflectance intensity in the NIR. NIR digital photography, therefore, provides the potential for rapid capture and quantitative analysis of spatial variations in stratigraphy along a trench face. NIR imagery is presented of snow trenches at Imnaviat Creek and Toolik Lake, Alaska, in February 2008 as part of the 2nd NASA Cold Land Processes Experiment. Issues involved in acquiring suitable images, stitching a series of adjacent images, picking stratigraphic layers, evaluating against manual stratigraphic observations and quantifying the uncertainties involved in each stage of the process are discussed.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2008
- Bibcode:
- 2008AGUFM.C34A..07R
- Keywords:
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- 0736 Snow (1827;
- 1863);
- 0794 Instruments and techniques