Measurement of snowpack density, grain size, and black carbon concentration using time-domain diffuse optics
Diffuse optical spectroscopy (DOS) techniques characterize scattering media by examining their optical response to laser illumination. Time-domain DOS methods involve illuminating the medium with a laser pulse and using a fast photodetector to measure the time-dependent intensity of light that exits...
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2025-01-01
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| Series: | Journal of Glaciology |
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| Online Access: | https://www.cambridge.org/core/product/identifier/S0022143024000819/type/journal_article |
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| _version_ | 1850278676986331136 |
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| author | Connor Andrew Henley Colin Richard Meyer Jacob Ian Chalif Joseph Lee Hollmann Ramesh Raskar |
| author_facet | Connor Andrew Henley Colin Richard Meyer Jacob Ian Chalif Joseph Lee Hollmann Ramesh Raskar |
| author_sort | Connor Andrew Henley |
| collection | DOAJ |
| description | Diffuse optical spectroscopy (DOS) techniques characterize scattering media by examining their optical response to laser illumination. Time-domain DOS methods involve illuminating the medium with a laser pulse and using a fast photodetector to measure the time-dependent intensity of light that exits the medium after multiple scattering events. While DOS research traditionally focused on characterizing biological tissues, we demonstrate that time-domain diffuse optical measurements can also be used to characterize snow. We introduce a model that predicts the time-dependent reflectance of a dry snowpack as a function of its density, grain size, and black carbon content. We develop an algorithm that retrieves these properties from measurements at two wavelengths. To validate our approach, we assembled a two-wavelength lidar system to measure the time-dependent reflectance of snow samples with varying properties. Rather than measuring direct surface returns, our system captures photons that enter and exit the snow at different points, separated by a small distance (4–10 cm). We observe clear, linear correlations between our retrievals of density and black carbon concentration, and ground truth. For black carbon concentration the correlation is nearly one-to-one. We also find that our method is capable of distinguishing between small and large grain sizes. |
| format | Article |
| id | doaj-art-9fc79641711e453983fdfd55c93d3107 |
| institution | OA Journals |
| issn | 0022-1430 1727-5652 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Journal of Glaciology |
| spelling | doaj-art-9fc79641711e453983fdfd55c93d31072025-08-20T01:49:23ZengCambridge University PressJournal of Glaciology0022-14301727-56522025-01-017110.1017/jog.2024.81Measurement of snowpack density, grain size, and black carbon concentration using time-domain diffuse opticsConnor Andrew Henley0https://orcid.org/0000-0002-9215-7245Colin Richard Meyer1Jacob Ian Chalif2Joseph Lee Hollmann3Ramesh Raskar4MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA The Charles Stark Draper Laboratory Inc, Cambridge, MA, USAThayer School of Engineering, Dartmouth College, Hanover, NH, USADepartment of Earth Sciences, Dartmouth College, Hanover, NH, USAThe Charles Stark Draper Laboratory Inc, Cambridge, MA, USAMIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USADiffuse optical spectroscopy (DOS) techniques characterize scattering media by examining their optical response to laser illumination. Time-domain DOS methods involve illuminating the medium with a laser pulse and using a fast photodetector to measure the time-dependent intensity of light that exits the medium after multiple scattering events. While DOS research traditionally focused on characterizing biological tissues, we demonstrate that time-domain diffuse optical measurements can also be used to characterize snow. We introduce a model that predicts the time-dependent reflectance of a dry snowpack as a function of its density, grain size, and black carbon content. We develop an algorithm that retrieves these properties from measurements at two wavelengths. To validate our approach, we assembled a two-wavelength lidar system to measure the time-dependent reflectance of snow samples with varying properties. Rather than measuring direct surface returns, our system captures photons that enter and exit the snow at different points, separated by a small distance (4–10 cm). We observe clear, linear correlations between our retrievals of density and black carbon concentration, and ground truth. For black carbon concentration the correlation is nearly one-to-one. We also find that our method is capable of distinguishing between small and large grain sizes.https://www.cambridge.org/core/product/identifier/S0022143024000819/type/journal_articleGlaciological instruments and methodsremote sensingsnow |
| spellingShingle | Connor Andrew Henley Colin Richard Meyer Jacob Ian Chalif Joseph Lee Hollmann Ramesh Raskar Measurement of snowpack density, grain size, and black carbon concentration using time-domain diffuse optics Journal of Glaciology Glaciological instruments and methods remote sensing snow |
| title | Measurement of snowpack density, grain size, and black carbon concentration using time-domain diffuse optics |
| title_full | Measurement of snowpack density, grain size, and black carbon concentration using time-domain diffuse optics |
| title_fullStr | Measurement of snowpack density, grain size, and black carbon concentration using time-domain diffuse optics |
| title_full_unstemmed | Measurement of snowpack density, grain size, and black carbon concentration using time-domain diffuse optics |
| title_short | Measurement of snowpack density, grain size, and black carbon concentration using time-domain diffuse optics |
| title_sort | measurement of snowpack density grain size and black carbon concentration using time domain diffuse optics |
| topic | Glaciological instruments and methods remote sensing snow |
| url | https://www.cambridge.org/core/product/identifier/S0022143024000819/type/journal_article |
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