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Estimation of Liquid Water Content of Snow Surface by Spectral Reflectance
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
Department of Civil and Transport Engineering, Norwegian Univ. of Science and Technology, NO-7491 Trondheim, Norway..
2018 (English)In: Journal of cold regions engineering, ISSN 0887-381X, E-ISSN 1943-5495, Vol. 32, no 1, 05018001Article in journal (Refereed) Published
Abstract [en]

This study measures the spectral reflectance from snow with known liquid water content (LWC) in a climate chamber using two optical sensors, a near-infrared (NIR) spectrometer and a Road eye sensor. The spectrometer measures the backscattered radiation in the wavelength range of 920–1,650 nm. The Road eye sensor was developed to monitor and classify winter roads based on reflected intensity measurements at wavelengths of 980, 1,310, and 1,550 nm. Results of the study suggest that the spectral reflectance from snow is inversely proportional to the LWC in snow. Based on the effect of LWC on the spectral reflectance, three optimum wavelength bands are selected in which snow with different LWCs is clearly distinguishable. A widely used remote sensing index known as the normalized difference water index (NDWI) is used to develop a method to estimate the surface LWC for a given snow pack. The derived NDWI values with respect to the known LWC in snow show that the NDWI is sensitive to the LWC in snow and that the NDWI and LWC are directly proportional. Based on this information, the NDWI is used to estimate the surface LWC in snow from measurements on a ski track using the Road eye sensor. The findings suggest that the presented method can be applied to estimate the surface LWC in order to classify snow conditions potentially for ski track and piste applications.

Place, publisher, year, edition, pages
American Society of Civil Engineers (ASCE), 2018. Vol. 32, no 1, 05018001
National Category
Applied Mechanics Geotechnical Engineering
Research subject
Experimental Mechanics; Soil Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-67197DOI: 10.1061/(ASCE)CR.1943-5495.0000158OAI: oai:DiVA.org:ltu-67197DiVA: diva2:1172032
Note

Validerad;2018;Nivå 2;2018-01-10 (andbra)

Available from: 2018-01-09 Created: 2018-01-09 Last updated: 2018-01-10Bibliographically approved

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