Reflectance Modeling for Real Snow Structures Using a Beam Tracing Model
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2008-05-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/8/5/3482/ |
| _version_ | 1798024549422333952 |
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| author | Martin Schneebeli Margret Matzl Claude Saskia Bourgeois Dominik Bänninger |
| author_facet | Martin Schneebeli Margret Matzl Claude Saskia Bourgeois Dominik Bänninger |
| author_sort | Martin Schneebeli |
| collection | DOAJ |
| description | 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 x 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. |
| first_indexed | 2024-04-11T18:04:27Z |
| format | Article |
| id | doaj.art-a514cf078384480cbbf3be6421ceab11 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T18:04:27Z |
| publishDate | 2008-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-a514cf078384480cbbf3be6421ceab112022-12-22T04:10:22ZengMDPI AGSensors1424-82202008-05-018534823496Reflectance Modeling for Real Snow Structures Using a Beam Tracing ModelMartin SchneebeliMargret MatzlClaude Saskia BourgeoisDominik BänningerIt 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 x 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.http://www.mdpi.com/1424-8220/8/5/3482/reflectanceradiative transfermodelingsnow |
| spellingShingle | Martin Schneebeli Margret Matzl Claude Saskia Bourgeois Dominik Bänninger Reflectance Modeling for Real Snow Structures Using a Beam Tracing Model Sensors reflectance radiative transfer modeling snow |
| title | Reflectance Modeling for Real Snow Structures Using a Beam Tracing Model |
| title_full | Reflectance Modeling for Real Snow Structures Using a Beam Tracing Model |
| title_fullStr | Reflectance Modeling for Real Snow Structures Using a Beam Tracing Model |
| title_full_unstemmed | Reflectance Modeling for Real Snow Structures Using a Beam Tracing Model |
| title_short | Reflectance Modeling for Real Snow Structures Using a Beam Tracing Model |
| title_sort | reflectance modeling for real snow structures using a beam tracing model |
| topic | reflectance radiative transfer modeling snow |
| url | http://www.mdpi.com/1424-8220/8/5/3482/ |
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