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Reflectance Modeling for Real Snow Structures Using a Beam Tracing Model

View Article: PubMed Central

ABSTRACT

It is important to understand reflective properties of snow, for example for remote sensing applications and for modeling of energy balances in snow packs. We present a method with which we can compare reflectance measurements and calculations for the same snow sample structures. Therefore, we first tomograph snow samples to acquire snow structure images (6 × 2 mm). Second, we calculated the sample reflectance by modeling the radiative transfer, using a beam tracing model. This model calculates the biconical reflectance (BR) derived from an arbitrary number of incident beams. The incident beams represent a diffuse light source. We applied our method to four different snow samples: Fresh snow, metamorphosed snow, depth hoar, and wet snow. The results show that (i) the calculated and measured reflectances agree well and (ii) the model produces different biconical reflectances for different snow types. The ratio of the structure to the wavelength is large. We estimated that the size parameter is larger than 50 in all cases we analyzed. Specific surface area of the snow samples explains most of the difference in radiance, but not the different biconical reflectance distributions. The presented method overcomes the limitations of common radiative transfer models which use idealized grain shapes such as spheres, plates, needles and hexagonal particles. With this method we could improve our understanding for changes in biconical reflectance distribution associated with changes in specific surface area.

No MeSH data available.


Related in: MedlinePlus

Measured reflectance spectra of the snow samples. The abbreviation behind the snow name is the class according to the international snow classification.
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f6-sensors-08-03482: Measured reflectance spectra of the snow samples. The abbreviation behind the snow name is the class according to the international snow classification.

Mentions: Table 1 summarizes the characteristics of the four snow samples which were collected in February 2006 in the area of Davos, Switzerland. Figure 5 shows for each snow sample a structure image recorded with the tomograph. In Figure 6 we plotted the measured reflectance spectra of these samples.


Reflectance Modeling for Real Snow Structures Using a Beam Tracing Model
Measured reflectance spectra of the snow samples. The abbreviation behind the snow name is the class according to the international snow classification.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3675556&req=5

f6-sensors-08-03482: Measured reflectance spectra of the snow samples. The abbreviation behind the snow name is the class according to the international snow classification.
Mentions: Table 1 summarizes the characteristics of the four snow samples which were collected in February 2006 in the area of Davos, Switzerland. Figure 5 shows for each snow sample a structure image recorded with the tomograph. In Figure 6 we plotted the measured reflectance spectra of these samples.

View Article: PubMed Central

ABSTRACT

It is important to understand reflective properties of snow, for example for remote sensing applications and for modeling of energy balances in snow packs. We present a method with which we can compare reflectance measurements and calculations for the same snow sample structures. Therefore, we first tomograph snow samples to acquire snow structure images (6 × 2 mm). Second, we calculated the sample reflectance by modeling the radiative transfer, using a beam tracing model. This model calculates the biconical reflectance (BR) derived from an arbitrary number of incident beams. The incident beams represent a diffuse light source. We applied our method to four different snow samples: Fresh snow, metamorphosed snow, depth hoar, and wet snow. The results show that (i) the calculated and measured reflectances agree well and (ii) the model produces different biconical reflectances for different snow types. The ratio of the structure to the wavelength is large. We estimated that the size parameter is larger than 50 in all cases we analyzed. Specific surface area of the snow samples explains most of the difference in radiance, but not the different biconical reflectance distributions. The presented method overcomes the limitations of common radiative transfer models which use idealized grain shapes such as spheres, plates, needles and hexagonal particles. With this method we could improve our understanding for changes in biconical reflectance distribution associated with changes in specific surface area.

No MeSH data available.


Related in: MedlinePlus