X-Ray Tomography-Based Microstructure Representation in the Snow Microwave Radiative Transfer Model
The modular Snow Microwave Radiative Transfer (SMRT) model simulates microwave scattering behavior in snow via different selectable theories and snow microstructure representations, which is well suited to intercomparisons analyses. Here, five microstructure models were parameterized from X-ray tomo...
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Veröffentlicht in: | IEEE transactions on geoscience and remote sensing 2022, Vol.60, p.1-15 |
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creator | Sandells, Melody Lowe, Henning Picard, Ghislain Dumont, Marie Essery, Richard Floury, Nicolas Kontu, Anna Lemmetyinen, Juha Maslanka, William Morin, Samuel Wiesmann, Andreas Matzler, Christian |
description | The modular Snow Microwave Radiative Transfer (SMRT) model simulates microwave scattering behavior in snow via different selectable theories and snow microstructure representations, which is well suited to intercomparisons analyses. Here, five microstructure models were parameterized from X-ray tomography and thin-section images of snow samples and evaluated with SMRT. Three field experiments provided observations of scattering and absorption coefficients, brightness temperature, and/or backscatter with the increasing complexity of snowpack. These took place in Sodankylä, Finland, and Weissfluhjoch, Switzerland. Simulations of scattering and absorption coefficients agreed well with observations, with higher errors for snow with predominantly vertical structures. For simulation of brightness temperature, difficulty in retrieving stickiness with the Sticky Hard Sphere microstructure model resulted in relatively poor performance for two experiments, but good agreement for the third. Exponential microstructure gave generally good results, near to the best performing models for two field experiments. The Independent Sphere model gave intermediate results. New Teubner-Strey and Gaussian Random Field models demonstrated the advantages of SMRT over microwave models with restricted microstructural geometry. Relative model performance is assessed by the quality of the microstructure model fit to micro-computed tomography (CT) data and further improvements may be possible with different fitting techniques. Careful consideration of simulation stratigraphy is required in this new era of high-resolution microstructure measurement as layers thinner than the wavelength introduce artificial scattering boundaries not seen by the instrument. |
doi_str_mv | 10.1109/TGRS.2021.3086412 |
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Here, five microstructure models were parameterized from X-ray tomography and thin-section images of snow samples and evaluated with SMRT. Three field experiments provided observations of scattering and absorption coefficients, brightness temperature, and/or backscatter with the increasing complexity of snowpack. These took place in Sodankylä, Finland, and Weissfluhjoch, Switzerland. Simulations of scattering and absorption coefficients agreed well with observations, with higher errors for snow with predominantly vertical structures. For simulation of brightness temperature, difficulty in retrieving stickiness with the Sticky Hard Sphere microstructure model resulted in relatively poor performance for two experiments, but good agreement for the third. Exponential microstructure gave generally good results, near to the best performing models for two field experiments. The Independent Sphere model gave intermediate results. New Teubner-Strey and Gaussian Random Field models demonstrated the advantages of SMRT over microwave models with restricted microstructural geometry. Relative model performance is assessed by the quality of the microstructure model fit to micro-computed tomography (CT) data and further improvements may be possible with different fitting techniques. Careful consideration of simulation stratigraphy is required in this new era of high-resolution microstructure measurement as layers thinner than the wavelength introduce artificial scattering boundaries not seen by the instrument.</description><identifier>ISSN: 0196-2892</identifier><identifier>EISSN: 1558-0644</identifier><identifier>DOI: 10.1109/TGRS.2021.3086412</identifier><identifier>CODEN: IGRSD2</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Absorption ; Absorptivity ; Backscattering ; Brightness ; Brightness temperature ; Coefficients ; Computed tomography ; Correlation ; Environmental Sciences ; Experiments ; Field tests ; Fields (mathematics) ; Mathematical models ; Meteorological satellites ; Microstructure ; Microwave radiometry ; Microwave scattering ; Microwave theory and techniques ; Object oriented modeling ; Quality assessment ; Radiative transfer ; Representations ; Scattering ; Simulation ; SMRT model ; Snow ; snow microwave radiative transfer (SMRT) ; Snowpack ; Stratigraphy ; Surface radiation temperature ; Tomography ; Wavelength ; X ray imagery ; X rays</subject><ispartof>IEEE transactions on geoscience and remote sensing, 2022, Vol.60, p.1-15</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><rights>Attribution</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c370t-8c82f72971051a3827c3042d496512274ecddb13bc169b68189056381df6d7f53</citedby><cites>FETCH-LOGICAL-c370t-8c82f72971051a3827c3042d496512274ecddb13bc169b68189056381df6d7f53</cites><orcidid>0000-0003-1475-5853 ; 0000-0002-4120-5163 ; 0000-0003-4434-9696 ; 0000-0001-6880-6260 ; 0000-0002-1777-733X ; 0000-0002-1781-687X ; 0000-0001-7380-8412 ; 0000-0003-1756-9095 ; 0000-0002-4002-5873</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9455876$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,792,881,4010,27900,27901,27902,54733</link.rule.ids><backlink>$$Uhttps://hal.science/hal-04389393$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Sandells, Melody</creatorcontrib><creatorcontrib>Lowe, Henning</creatorcontrib><creatorcontrib>Picard, Ghislain</creatorcontrib><creatorcontrib>Dumont, Marie</creatorcontrib><creatorcontrib>Essery, Richard</creatorcontrib><creatorcontrib>Floury, Nicolas</creatorcontrib><creatorcontrib>Kontu, Anna</creatorcontrib><creatorcontrib>Lemmetyinen, Juha</creatorcontrib><creatorcontrib>Maslanka, William</creatorcontrib><creatorcontrib>Morin, Samuel</creatorcontrib><creatorcontrib>Wiesmann, Andreas</creatorcontrib><creatorcontrib>Matzler, Christian</creatorcontrib><title>X-Ray Tomography-Based Microstructure Representation in the Snow Microwave Radiative Transfer Model</title><title>IEEE transactions on geoscience and remote sensing</title><addtitle>TGRS</addtitle><description>The modular Snow Microwave Radiative Transfer (SMRT) model simulates microwave scattering behavior in snow via different selectable theories and snow microstructure representations, which is well suited to intercomparisons analyses. Here, five microstructure models were parameterized from X-ray tomography and thin-section images of snow samples and evaluated with SMRT. Three field experiments provided observations of scattering and absorption coefficients, brightness temperature, and/or backscatter with the increasing complexity of snowpack. These took place in Sodankylä, Finland, and Weissfluhjoch, Switzerland. Simulations of scattering and absorption coefficients agreed well with observations, with higher errors for snow with predominantly vertical structures. For simulation of brightness temperature, difficulty in retrieving stickiness with the Sticky Hard Sphere microstructure model resulted in relatively poor performance for two experiments, but good agreement for the third. Exponential microstructure gave generally good results, near to the best performing models for two field experiments. The Independent Sphere model gave intermediate results. New Teubner-Strey and Gaussian Random Field models demonstrated the advantages of SMRT over microwave models with restricted microstructural geometry. Relative model performance is assessed by the quality of the microstructure model fit to micro-computed tomography (CT) data and further improvements may be possible with different fitting techniques. Careful consideration of simulation stratigraphy is required in this new era of high-resolution microstructure measurement as layers thinner than the wavelength introduce artificial scattering boundaries not seen by the instrument.</description><subject>Absorption</subject><subject>Absorptivity</subject><subject>Backscattering</subject><subject>Brightness</subject><subject>Brightness temperature</subject><subject>Coefficients</subject><subject>Computed tomography</subject><subject>Correlation</subject><subject>Environmental Sciences</subject><subject>Experiments</subject><subject>Field tests</subject><subject>Fields (mathematics)</subject><subject>Mathematical models</subject><subject>Meteorological satellites</subject><subject>Microstructure</subject><subject>Microwave radiometry</subject><subject>Microwave scattering</subject><subject>Microwave theory and techniques</subject><subject>Object oriented modeling</subject><subject>Quality assessment</subject><subject>Radiative transfer</subject><subject>Representations</subject><subject>Scattering</subject><subject>Simulation</subject><subject>SMRT model</subject><subject>Snow</subject><subject>snow microwave radiative transfer (SMRT)</subject><subject>Snowpack</subject><subject>Stratigraphy</subject><subject>Surface radiation temperature</subject><subject>Tomography</subject><subject>Wavelength</subject><subject>X ray imagery</subject><subject>X rays</subject><issn>0196-2892</issn><issn>1558-0644</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><recordid>eNo9kVFLwzAQgIMoOKc_QHwp-ORDZy5J0-RxDt2EDWGr4FvI2tR1bE1N2o39e1s69nTH3XfH8R1Cj4BHAFi-JtPlakQwgRHFgjMgV2gAUSRCzBm7RgMMkodESHKL7rzfYgwsgniA0p9wqU9BYvf21-lqcwrftDdZsChSZ33tmrRunAmWpnLGm7LWdWHLoCiDemOCVWmPPXnUhxbSWdH22yxxuvS5ccHCZmZ3j25yvfPm4RyH6PvjPZnMwvnX9HMynocpjXEdilSQPCYyBhyBpoLEKcWMZEzyCAiJmUmzbA10nQKXay5ASBxxKiDLeRbnER2il37vRu9U5Yq9didldaFm47nqaphRIamkB2jZ556tnP1rjK_V1jaubM9ThIPEhMgWHSLoqU6Gdya_rAWsOu-q86467-rsvZ156mcKY8yFl6x9RszpP-jffUM</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Sandells, Melody</creator><creator>Lowe, Henning</creator><creator>Picard, Ghislain</creator><creator>Dumont, Marie</creator><creator>Essery, Richard</creator><creator>Floury, Nicolas</creator><creator>Kontu, Anna</creator><creator>Lemmetyinen, Juha</creator><creator>Maslanka, William</creator><creator>Morin, Samuel</creator><creator>Wiesmann, Andreas</creator><creator>Matzler, Christian</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><general>Institute of Electrical and Electronics Engineers</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0003-1475-5853</orcidid><orcidid>https://orcid.org/0000-0002-4120-5163</orcidid><orcidid>https://orcid.org/0000-0003-4434-9696</orcidid><orcidid>https://orcid.org/0000-0001-6880-6260</orcidid><orcidid>https://orcid.org/0000-0002-1777-733X</orcidid><orcidid>https://orcid.org/0000-0002-1781-687X</orcidid><orcidid>https://orcid.org/0000-0001-7380-8412</orcidid><orcidid>https://orcid.org/0000-0003-1756-9095</orcidid><orcidid>https://orcid.org/0000-0002-4002-5873</orcidid></search><sort><creationdate>2022</creationdate><title>X-Ray Tomography-Based Microstructure Representation in the Snow Microwave Radiative Transfer Model</title><author>Sandells, Melody ; Lowe, Henning ; Picard, Ghislain ; Dumont, Marie ; Essery, Richard ; Floury, Nicolas ; Kontu, Anna ; Lemmetyinen, Juha ; Maslanka, William ; Morin, Samuel ; Wiesmann, Andreas ; Matzler, Christian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c370t-8c82f72971051a3827c3042d496512274ecddb13bc169b68189056381df6d7f53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Absorption</topic><topic>Absorptivity</topic><topic>Backscattering</topic><topic>Brightness</topic><topic>Brightness temperature</topic><topic>Coefficients</topic><topic>Computed tomography</topic><topic>Correlation</topic><topic>Environmental Sciences</topic><topic>Experiments</topic><topic>Field tests</topic><topic>Fields (mathematics)</topic><topic>Mathematical models</topic><topic>Meteorological satellites</topic><topic>Microstructure</topic><topic>Microwave radiometry</topic><topic>Microwave scattering</topic><topic>Microwave theory and techniques</topic><topic>Object oriented modeling</topic><topic>Quality assessment</topic><topic>Radiative transfer</topic><topic>Representations</topic><topic>Scattering</topic><topic>Simulation</topic><topic>SMRT model</topic><topic>Snow</topic><topic>snow microwave radiative transfer (SMRT)</topic><topic>Snowpack</topic><topic>Stratigraphy</topic><topic>Surface radiation temperature</topic><topic>Tomography</topic><topic>Wavelength</topic><topic>X ray imagery</topic><topic>X rays</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sandells, Melody</creatorcontrib><creatorcontrib>Lowe, Henning</creatorcontrib><creatorcontrib>Picard, Ghislain</creatorcontrib><creatorcontrib>Dumont, Marie</creatorcontrib><creatorcontrib>Essery, Richard</creatorcontrib><creatorcontrib>Floury, Nicolas</creatorcontrib><creatorcontrib>Kontu, Anna</creatorcontrib><creatorcontrib>Lemmetyinen, Juha</creatorcontrib><creatorcontrib>Maslanka, William</creatorcontrib><creatorcontrib>Morin, Samuel</creatorcontrib><creatorcontrib>Wiesmann, Andreas</creatorcontrib><creatorcontrib>Matzler, Christian</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>IEEE transactions on geoscience and remote sensing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sandells, Melody</au><au>Lowe, Henning</au><au>Picard, Ghislain</au><au>Dumont, Marie</au><au>Essery, Richard</au><au>Floury, Nicolas</au><au>Kontu, Anna</au><au>Lemmetyinen, Juha</au><au>Maslanka, William</au><au>Morin, Samuel</au><au>Wiesmann, Andreas</au><au>Matzler, Christian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>X-Ray Tomography-Based Microstructure Representation in the Snow Microwave Radiative Transfer Model</atitle><jtitle>IEEE transactions on geoscience and remote sensing</jtitle><stitle>TGRS</stitle><date>2022</date><risdate>2022</risdate><volume>60</volume><spage>1</spage><epage>15</epage><pages>1-15</pages><issn>0196-2892</issn><eissn>1558-0644</eissn><coden>IGRSD2</coden><abstract>The modular Snow Microwave Radiative Transfer (SMRT) model simulates microwave scattering behavior in snow via different selectable theories and snow microstructure representations, which is well suited to intercomparisons analyses. Here, five microstructure models were parameterized from X-ray tomography and thin-section images of snow samples and evaluated with SMRT. Three field experiments provided observations of scattering and absorption coefficients, brightness temperature, and/or backscatter with the increasing complexity of snowpack. These took place in Sodankylä, Finland, and Weissfluhjoch, Switzerland. Simulations of scattering and absorption coefficients agreed well with observations, with higher errors for snow with predominantly vertical structures. For simulation of brightness temperature, difficulty in retrieving stickiness with the Sticky Hard Sphere microstructure model resulted in relatively poor performance for two experiments, but good agreement for the third. Exponential microstructure gave generally good results, near to the best performing models for two field experiments. The Independent Sphere model gave intermediate results. New Teubner-Strey and Gaussian Random Field models demonstrated the advantages of SMRT over microwave models with restricted microstructural geometry. Relative model performance is assessed by the quality of the microstructure model fit to micro-computed tomography (CT) data and further improvements may be possible with different fitting techniques. Careful consideration of simulation stratigraphy is required in this new era of high-resolution microstructure measurement as layers thinner than the wavelength introduce artificial scattering boundaries not seen by the instrument.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TGRS.2021.3086412</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0003-1475-5853</orcidid><orcidid>https://orcid.org/0000-0002-4120-5163</orcidid><orcidid>https://orcid.org/0000-0003-4434-9696</orcidid><orcidid>https://orcid.org/0000-0001-6880-6260</orcidid><orcidid>https://orcid.org/0000-0002-1777-733X</orcidid><orcidid>https://orcid.org/0000-0002-1781-687X</orcidid><orcidid>https://orcid.org/0000-0001-7380-8412</orcidid><orcidid>https://orcid.org/0000-0003-1756-9095</orcidid><orcidid>https://orcid.org/0000-0002-4002-5873</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Absorption Absorptivity Backscattering Brightness Brightness temperature Coefficients Computed tomography Correlation Environmental Sciences Experiments Field tests Fields (mathematics) Mathematical models Meteorological satellites Microstructure Microwave radiometry Microwave scattering Microwave theory and techniques Object oriented modeling Quality assessment Radiative transfer Representations Scattering Simulation SMRT model Snow snow microwave radiative transfer (SMRT) Snowpack Stratigraphy Surface radiation temperature Tomography Wavelength X ray imagery X rays |
title | X-Ray Tomography-Based Microstructure Representation in the Snow Microwave Radiative Transfer Model |
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