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Geosciences 2018, 8(11), 404; https://doi.org/10.3390/geosciences8110404

Analysis of QualitySpec Trek Reflectance from Vertical Profiles of Taiga Snowpack

Finnish Meteorological Institute, Space and Earth Observation Centre, Tähteläntie 62, 99600 Sodankylä, Finland
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Received: 20 September 2018 / Revised: 26 October 2018 / Accepted: 1 November 2018 / Published: 6 November 2018
(This article belongs to the Special Issue Remote Sensing of Snow and Its Applications)
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Abstract

Snow microstructure is an important factor for microwave and optical remote sensing of snow. One parameter used to describe it is the specific surface area (SSA), which is defined as the surface-area-to-mass ratio of snow grains. Reflectance at near infrared (NIR) and short-wave infrared (SWIR) wavelengths is sensitive to grain size and therefore also to SSA through the theoretical relationship between SSA and optical equivalent grain size. To observe SSA, the IceCube measures the hemispherical reflectance of a 1310 nm laser diode from the snow sample surface. The recently developed hand-held QualitySpec Trek (QST) instrument measures the almost bidirectional spectral reflectance in the range of 350–2500 nm with direct contact to the object. The geometry is similar to the Contact Probe, which was previously used successfully for snow measurements. The collected data set includes five snow pit measurements made using both IceCube and QST in a taiga snowpack in spring 2017 in Sodankylä, Finland. In this study, the correlation between SSA and a ratio of 1260 nm reflectance to differentiate between 1260 nm and 1160 nm reflectances is researched. The correlation coefficient varied between 0.85 and 0.98, which demonstrates an empirical linear relationship between SSA and reflectance observations of QST. View Full-Text
Keywords: near-infrared reflectance; specific surface area; spectrometer; snow microstructure near-infrared reflectance; specific surface area; spectrometer; snow microstructure
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Leppänen, L.; Kontu, A. Analysis of QualitySpec Trek Reflectance from Vertical Profiles of Taiga Snowpack. Geosciences 2018, 8, 404.

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