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Estimation of specific surface area of snow based on density and multispectral infrared reflectance
Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Strömningslära och experimentell mekanik. (Experimental mechanics)ORCID-id: 0000-0002-5943-1476
Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Strömningslära och experimentell mekanik. (Experimental mechanics)
Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Strömningslära och experimentell mekanik. (Experimental mechanics)
(engelsk)Inngår i: Journal of cold regions engineering, ISSN 0887-381X, E-ISSN 1943-5495Artikkel i tidsskrift (Fagfellevurdert) Submitted
Abstract [en]

This paper presents a multiple regression method for predicting snow SSA based on multispectral reflectance and snow density. Multispectral near-IR reflectance from snow was measured at wavelengths 980 nm, 1,310 nm and 1,550 nm. In total, 16 different artificially prepared snow samples were investigated using two optical sensors, a spectrometer and a Road eye sensor. Both the sensors measured backscattered radiance from snow and measurements were carried out in a climate chamber.  Snow types with variations in physical properties such as grain distribution, surface texture, SSA, density and depth are considered. Variations in snow density were obtained through compaction and aging process. Correlation between the snow density and reflectance is investigated and influence of snow density and multispectral reflectance on snow SSA is also investigated. A generalized linear model is developed to predict the snow SSA with a coefficient of determination equal to 98\%. The preliminary validation of results show that the SSA can be accurately estimated from the density and multispectral reflectance. The model results indicate that the snow density has minor effect on the variations in snow SSA. Results suggest that snow with varying physical properties can be qualitatively characterized based on the presented approach, which is of interest for applications such as winter roads classification and pistes classification.  

Emneord [en]
Snow reflectance, Specific surface area, snow density, Parameterization, Spectrometer, Road eye
HSV kategori
Forskningsprogram
Experimentell mekanik
Identifikatorer
URN: urn:nbn:se:ltu:diva-68398OAI: oai:DiVA.org:ltu-68398DiVA, id: diva2:1198493
Tilgjengelig fra: 2018-04-17 Laget: 2018-04-17 Sist oppdatert: 2019-09-11
Inngår i avhandling
1. Experimental investigation of snow metamorphism at near-surface layers
Åpne denne publikasjonen i ny fane eller vindu >>Experimental investigation of snow metamorphism at near-surface layers
2018 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Alternativ tittel[sv]
Experimentell undersökning avsnömetamorfismen vid nära ytskikt
Abstract [en]

Snow metamorphism is a direct objective in many snow research areas, and its charac-terisation is a major challenge in areas including winter road maintenance, detection of icing on wind turbine blades, and snow quality mapping for skiing. A common effect of snow metamorphism is compaction, which can be investigated from the associated vari-ations in physical properties of snow. While the relation between snow metamorphism and physical properties of snow is fairly well-known, a method to quantify this relationis not extensively researched. This experimental based thesis focuses on the relationship between the physical properties of snow and its degree of metamorphism. The link isestablished and investigated by quantifying near-infrared (NIR) reflectance measure-ments and analysing the microtomographic data. Three experimental approaches are developed to record the NIR reflectance measurements and to understand the influence of compaction at near-surface layers of a snowpack. In addition, an X-ray microtomogra-phy (micro-CT) system is used to visualise the behaviour of snow microstructure during compaction. In this thesis, snow experienced compaction via aging, the melting-freezing process, uniaxial loading, settling and infiltration of liquid water.

A numerical tool based on the well-established Discrete Ordinates Radiative Trans-fer (DISORT) method is used to solve the radiative transfer equation (RTE) for aplane-parallel and semi-infinite snowpack. The numerical solver takes the reflectance measurements as input and returns the coefficients of a first order Legendre phase function of an investigated snowpack at a given wavelength of light. The results from the solver show consistency and strong correlation between the Legendre coefficient sand the physical properties of snow. Furthermore, the physical properties of snow such as specific surface area (SSA) and liquid water content (LWC) were estimated via parameterisation where the reflectance data is used as input. The results suggest that the parameterisation of LWC can provide a qualitative estimate of the LWC in a snowpack, while the parameterisation of SSA provides a quantitative estimate of the snow SSA. As a next step, the influence of compaction on snow microstructure is investigated from three-dimensional (3D) images obtained using the micro-CT system. In this case, compaction is initiated by applying uniaxial load on a snow sample and the effect of compaction is analysed based on digital volume correlation (DVC) and porosity distribution. The micro-CT observations further emphasise that near-surface layers of a snowpack experience a higher degree of impact during compaction.

In summary, this thesis presents experimental methods to quantify the link between snow compaction at near-surface layers, and the physical properties of snow. The mode observations show that the estimated Legendre coefficients can provide qualitative descriptions of snow grain distribution and surface texture. The parameterisation methods can provide the details about the LWC and the SSA of a snowpack. Further, the observations from the micro-CT study suggest that grains breakage and recrystallisation are the prevailing effects of snow compaction. All observations in this thesis are helpful in understanding the metamorphism in a snowpack for relevant research areas.

sted, utgiver, år, opplag, sider
Luleå: Luleå University of Technology, 2018
Serie
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Emneord
Snow metamorphism, NIR reflectance, Snow and Ice, Radiative transfer equation, Paramterization, Snow properties, Tomography, Snow microstructure
HSV kategori
Forskningsprogram
Experimentell mekanik
Identifikatorer
urn:nbn:se:ltu:diva-68394 (URN)978-91-7790-116-7 (ISBN)978-91-7790-117-4 (ISBN)
Disputas
2018-06-18, E 231, Luleå University of Technology, Luleå, 14:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2018-04-18 Laget: 2018-04-18 Sist oppdatert: 2019-09-11bibliografisk kontrollert

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