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Estimation of specific surface area of snow based on density and multispectral infrared reflectance
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics. (Experimental mechanics)ORCID iD: 0000-0002-5943-1476
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics. (Experimental mechanics)
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics. (Experimental mechanics)
(English)In: Journal of cold regions engineering, ISSN 0887-381X, E-ISSN 1943-5495Article in journal (Refereed) 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.  

Keyword [en]
Snow reflectance; Specific surface area; snow density; Parameterization; Spectrometer; Road eye
National Category
Other Materials Engineering
Research subject
Experimental Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-68398OAI: oai:DiVA.org:ltu-68398DiVA, id: diva2:1198493
Available from: 2018-04-17 Created: 2018-04-17 Last updated: 2018-04-25
In thesis
1. Experimental investigation of snow metamorphism at near-surface layers
Open this publication in new window or tab >>Experimental investigation of snow metamorphism at near-surface layers
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Snow metamorphism is a direct objective in many snow research areas, and its charactization is a major challenge in areas including winter road maintenance, detection of icing on wind turbine blades and snow quality mapping for skiing. The snow metamorphism in response to level and type of compaction associated with variations in physical properties of snow. While the compaction influence on snow metamorphism in relation to snow physical properties is fairly known, the relation between the compaction and physical properties of snow is not extensively understood. This experimental based thesis study presents three different approaches to investigate the snow metamorphism in response to compaction. Considered snow types during the thesis, experienced compaction via aging, melting-freezing process, applying uniaxial load, settling and introducing liquid water. In addition, the influence of snow compaction at near-surface layers is investigated using optical techniques.

In the first approach, near-infrared (NIR) light scattering from snow surfaces is numerically modelled based on the radiative transfer theory. The model used in this approach, was a special case of widely used Discrete Ordinates Radiative Transfer (DISORT) method that solves the radiative transfer equation for a plane-parallel and semi-infinite snowpack. This numerical methodology leads to a Legendre scattering phase function, where the link between the Legendre coefficients and physical properties of snow in relation to compaction is investigated. The observations in this approach show the consistency and strong correlation between the Legendre coefficients and physical properties of snow. The second approach of the thesis, was focused on statistical analysis of NIR reflectance measurements from snow surfaces for the determination of snow properties. In this approach, physical properties of snow such as specific surface area (SSA) and surface liquid water content (LWC) are quantified via parameterization where the reflectance data is used as input. In both of these approaches, compaction of a snowpack is investigated and understood based on grain size distribution, surface texture, snow temperature and scattering behaviour of NIR radiation. As a next step, the snow compaction is investigated on a microscopic level where a X-ray microtomography (micro-CT) was used to model the three dimensional (3D) microstructure of snow. In this approach, evolution and deformation of snow grains during compaction via applying uniaxial load is investigated. In addition, snow compaction is understood based on digital volume correlation (DVC) and porosity analysis.

In summary, the thesis presents an experimental method to quantify the link between the snow compaction at near-surface layers and physical properties of snow. The model observations show that the estimated Legendre coefficients can provide qualitative description of snow grain distribution and surface texture. The parameterization observations show that the SSA of snow and snow surface LWC can be quantified from snow reflectance measurements. The observations from the micro-CT study show the influence of compaction at a granular level. The observations presented in the thesis, are helpful to understand the metamorphism in a snowpack for relevant research areas.

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2018
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Keyword
Snow metamorphism; NIR reflectance; Snow and Ice; Radiative transfer equation; Paramterization; Snow properties; Tomography; Snow microstructure
National Category
Other Materials Engineering Applied Mechanics
Research subject
Experimental Mechanics
Identifiers
urn:nbn:se:ltu:diva-68394 (URN)978-91-7790-116-7 (ISBN)978-91-7790-117-4 (ISBN)
Public defence
2018-06-18, E231, Luleå University of Technology, Luleå, 15:48 (English)
Opponent
Supervisors
Available from: 2018-04-18 Created: 2018-04-18 Last updated: 2018-04-18Bibliographically approved

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