Downscaling SMOS-Derived Soil Moisture Using MODIS Visible/Infrared Data
A downscaling approach to improve the spatial resolution of Soil Moisture and Ocean Salinity (SMOS) soil moisture estimates with the use of higher resolution visible/infrared (VIS/IR) satellite data is presented. The algorithm is based on the so-called "universal triangle" concept that rel...
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| Veröffentlicht in: | IEEE transactions on geoscience and remote sensing 2011-09, Vol.49 (9), p.3156-3166 |
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| creator | Piles, M. Camps, A. Vall-llossera, M. Corbella, I. Panciera, R. Rudiger, C. Kerr, Y. H. Walker, J. |
| description | A downscaling approach to improve the spatial resolution of Soil Moisture and Ocean Salinity (SMOS) soil moisture estimates with the use of higher resolution visible/infrared (VIS/IR) satellite data is presented. The algorithm is based on the so-called "universal triangle" concept that relates VIS/IR parameters, such as the Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature ( T s ), to the soil moisture status. It combines the accuracy of SMOS observations with the high spatial resolution of VIS/IR satellite data into accurate soil moisture estimates at high spatial resolution. In preparation for the SMOS launch, the algorithm was tested using observations of the UPC Airborne RadIomEter at L-band (ARIEL) over the Soil Moisture Measurement Network of the University of Salamanca (REMEDHUS) in Zamora (Spain), and LANDSAT imagery. Results showed fairly good agreement with ground-based soil moisture measurements and illustrated the strength of the link between VIS/IR satellite data and soil moisture status. Following the SMOS launch, a downscaling strategy for the estimation of soil moisture at high resolution from SMOS using MODIS VIS/IR data has been developed. The method has been applied to some of the first SMOS images acquired during the commissioning phase and is validated against in situ soil moisture data from the OZnet soil moisture monitoring network, in South-Eastern Australia. Results show that the soil moisture variability is effectively captured at 10 and 1 km spatial scales without a significant degradation of the root mean square error. |
| doi_str_mv | 10.1109/TGRS.2011.2120615 |
| format | Article |
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H. ; Walker, J.</creator><creatorcontrib>Piles, M. ; Camps, A. ; Vall-llossera, M. ; Corbella, I. ; Panciera, R. ; Rudiger, C. ; Kerr, Y. H. ; Walker, J.</creatorcontrib><description>A downscaling approach to improve the spatial resolution of Soil Moisture and Ocean Salinity (SMOS) soil moisture estimates with the use of higher resolution visible/infrared (VIS/IR) satellite data is presented. The algorithm is based on the so-called "universal triangle" concept that relates VIS/IR parameters, such as the Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature ( T s ), to the soil moisture status. It combines the accuracy of SMOS observations with the high spatial resolution of VIS/IR satellite data into accurate soil moisture estimates at high spatial resolution. In preparation for the SMOS launch, the algorithm was tested using observations of the UPC Airborne RadIomEter at L-band (ARIEL) over the Soil Moisture Measurement Network of the University of Salamanca (REMEDHUS) in Zamora (Spain), and LANDSAT imagery. Results showed fairly good agreement with ground-based soil moisture measurements and illustrated the strength of the link between VIS/IR satellite data and soil moisture status. Following the SMOS launch, a downscaling strategy for the estimation of soil moisture at high resolution from SMOS using MODIS VIS/IR data has been developed. The method has been applied to some of the first SMOS images acquired during the commissioning phase and is validated against in situ soil moisture data from the OZnet soil moisture monitoring network, in South-Eastern Australia. Results show that the soil moisture variability is effectively captured at 10 and 1 km spatial scales without a significant degradation of the root mean square error.</description><identifier>ISSN: 0196-2892</identifier><identifier>EISSN: 1558-0644</identifier><identifier>DOI: 10.1109/TGRS.2011.2120615</identifier><identifier>CODEN: IGRSD2</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Applied geophysics ; Downscaling algorithm ; Earth sciences ; Earth, ocean, space ; Enginyeria de la telecomunicació ; Exact sciences and technology ; Internal geophysics ; Joining processes ; Mesurament ; Microones ; Microwave measurements ; MODIS ; passive microwave remote sensing ; Radiocomunicació i exploració electromagnètica ; Satellites ; Satèl·lits i ràdioenllaços ; Sistemes d'informació geogràfica ; SMOS ; Soil moisture ; Spatial resolution ; Vegetation mapping ; Àrees temàtiques de la UPC</subject><ispartof>IEEE transactions on geoscience and remote sensing, 2011-09, Vol.49 (9), p.3156-3166</ispartof><rights>2015 INIST-CNRS</rights><rights>info:eu-repo/semantics/openAccess</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c403t-fc9c2db65d6d604e92f7ee94902c145fabbf3951fe77daeda39c74129e1b61c63</citedby><cites>FETCH-LOGICAL-c403t-fc9c2db65d6d604e92f7ee94902c145fabbf3951fe77daeda39c74129e1b61c63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5756664$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,309,310,314,780,784,789,790,796,885,23930,23931,25140,26974,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5756664$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24473389$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Piles, M.</creatorcontrib><creatorcontrib>Camps, A.</creatorcontrib><creatorcontrib>Vall-llossera, M.</creatorcontrib><creatorcontrib>Corbella, I.</creatorcontrib><creatorcontrib>Panciera, R.</creatorcontrib><creatorcontrib>Rudiger, C.</creatorcontrib><creatorcontrib>Kerr, Y. H.</creatorcontrib><creatorcontrib>Walker, J.</creatorcontrib><title>Downscaling SMOS-Derived Soil Moisture Using MODIS Visible/Infrared Data</title><title>IEEE transactions on geoscience and remote sensing</title><addtitle>TGRS</addtitle><description>A downscaling approach to improve the spatial resolution of Soil Moisture and Ocean Salinity (SMOS) soil moisture estimates with the use of higher resolution visible/infrared (VIS/IR) satellite data is presented. The algorithm is based on the so-called "universal triangle" concept that relates VIS/IR parameters, such as the Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature ( T s ), to the soil moisture status. It combines the accuracy of SMOS observations with the high spatial resolution of VIS/IR satellite data into accurate soil moisture estimates at high spatial resolution. In preparation for the SMOS launch, the algorithm was tested using observations of the UPC Airborne RadIomEter at L-band (ARIEL) over the Soil Moisture Measurement Network of the University of Salamanca (REMEDHUS) in Zamora (Spain), and LANDSAT imagery. Results showed fairly good agreement with ground-based soil moisture measurements and illustrated the strength of the link between VIS/IR satellite data and soil moisture status. Following the SMOS launch, a downscaling strategy for the estimation of soil moisture at high resolution from SMOS using MODIS VIS/IR data has been developed. The method has been applied to some of the first SMOS images acquired during the commissioning phase and is validated against in situ soil moisture data from the OZnet soil moisture monitoring network, in South-Eastern Australia. Results show that the soil moisture variability is effectively captured at 10 and 1 km spatial scales without a significant degradation of the root mean square error.</description><subject>Applied geophysics</subject><subject>Downscaling algorithm</subject><subject>Earth sciences</subject><subject>Earth, ocean, space</subject><subject>Enginyeria de la telecomunicació</subject><subject>Exact sciences and technology</subject><subject>Internal geophysics</subject><subject>Joining processes</subject><subject>Mesurament</subject><subject>Microones</subject><subject>Microwave measurements</subject><subject>MODIS</subject><subject>passive microwave remote sensing</subject><subject>Radiocomunicació i exploració electromagnètica</subject><subject>Satellites</subject><subject>Satèl·lits i ràdioenllaços</subject><subject>Sistemes d'informació geogràfica</subject><subject>SMOS</subject><subject>Soil moisture</subject><subject>Spatial resolution</subject><subject>Vegetation mapping</subject><subject>Àrees temàtiques de la UPC</subject><issn>0196-2892</issn><issn>1558-0644</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>XX2</sourceid><recordid>eNpFkE1Lw0AQhhdRsFZ_gHjJxWPanc1mkz1Ko22hpWBar8tmM5GVmJTdVPHfm9DSHoZhmPedj4eQR6ATACqn2_l7PmEUYMKAUQHxFRlBHKchFZxfkxEFKUKWSnZL7rz_ohR4DMmILLL2t_FG17b5DPL1Jg8zdPYHyyBvbR2sW-u7g8Ng5wfBepMt8-DDelvUOF02ldOul2a60_fkptK1x4dTHpPd2-t2tghXm_ly9rIKDadRF1ZGGlYWIi5FKShHyaoEUXJJmelPqnRRVJGMocIkKTWWOpIm4cAkQiHAiGhM4DjX-INRDg06ozvVansphmA0YQpSzvq1F49rvXdYqb2z39r9KaBqwKcGfGrAp074es_z0bPXA57-08ZYfzYyzpMoSmWvezrqLCKe23ESCyF49A-QQHf0</recordid><startdate>20110901</startdate><enddate>20110901</enddate><creator>Piles, M.</creator><creator>Camps, A.</creator><creator>Vall-llossera, M.</creator><creator>Corbella, I.</creator><creator>Panciera, R.</creator><creator>Rudiger, C.</creator><creator>Kerr, Y. H.</creator><creator>Walker, J.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>IEEE Press. Institute of Electrical and Electronics Engineers</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>XX2</scope></search><sort><creationdate>20110901</creationdate><title>Downscaling SMOS-Derived Soil Moisture Using MODIS Visible/Infrared Data</title><author>Piles, M. ; Camps, A. ; Vall-llossera, M. ; Corbella, I. ; Panciera, R. ; Rudiger, C. ; Kerr, Y. H. ; Walker, J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c403t-fc9c2db65d6d604e92f7ee94902c145fabbf3951fe77daeda39c74129e1b61c63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Applied geophysics</topic><topic>Downscaling algorithm</topic><topic>Earth sciences</topic><topic>Earth, ocean, space</topic><topic>Enginyeria de la telecomunicació</topic><topic>Exact sciences and technology</topic><topic>Internal geophysics</topic><topic>Joining processes</topic><topic>Mesurament</topic><topic>Microones</topic><topic>Microwave measurements</topic><topic>MODIS</topic><topic>passive microwave remote sensing</topic><topic>Radiocomunicació i exploració electromagnètica</topic><topic>Satellites</topic><topic>Satèl·lits i ràdioenllaços</topic><topic>Sistemes d'informació geogràfica</topic><topic>SMOS</topic><topic>Soil moisture</topic><topic>Spatial resolution</topic><topic>Vegetation mapping</topic><topic>Àrees temàtiques de la UPC</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Piles, M.</creatorcontrib><creatorcontrib>Camps, A.</creatorcontrib><creatorcontrib>Vall-llossera, M.</creatorcontrib><creatorcontrib>Corbella, I.</creatorcontrib><creatorcontrib>Panciera, R.</creatorcontrib><creatorcontrib>Rudiger, C.</creatorcontrib><creatorcontrib>Kerr, Y. H.</creatorcontrib><creatorcontrib>Walker, J.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005–Present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Recercat</collection><jtitle>IEEE transactions on geoscience and remote sensing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Piles, M.</au><au>Camps, A.</au><au>Vall-llossera, M.</au><au>Corbella, I.</au><au>Panciera, R.</au><au>Rudiger, C.</au><au>Kerr, Y. H.</au><au>Walker, J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Downscaling SMOS-Derived Soil Moisture Using MODIS Visible/Infrared Data</atitle><jtitle>IEEE transactions on geoscience and remote sensing</jtitle><stitle>TGRS</stitle><date>2011-09-01</date><risdate>2011</risdate><volume>49</volume><issue>9</issue><spage>3156</spage><epage>3166</epage><pages>3156-3166</pages><issn>0196-2892</issn><eissn>1558-0644</eissn><coden>IGRSD2</coden><abstract>A downscaling approach to improve the spatial resolution of Soil Moisture and Ocean Salinity (SMOS) soil moisture estimates with the use of higher resolution visible/infrared (VIS/IR) satellite data is presented. The algorithm is based on the so-called "universal triangle" concept that relates VIS/IR parameters, such as the Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature ( T s ), to the soil moisture status. It combines the accuracy of SMOS observations with the high spatial resolution of VIS/IR satellite data into accurate soil moisture estimates at high spatial resolution. In preparation for the SMOS launch, the algorithm was tested using observations of the UPC Airborne RadIomEter at L-band (ARIEL) over the Soil Moisture Measurement Network of the University of Salamanca (REMEDHUS) in Zamora (Spain), and LANDSAT imagery. Results showed fairly good agreement with ground-based soil moisture measurements and illustrated the strength of the link between VIS/IR satellite data and soil moisture status. Following the SMOS launch, a downscaling strategy for the estimation of soil moisture at high resolution from SMOS using MODIS VIS/IR data has been developed. The method has been applied to some of the first SMOS images acquired during the commissioning phase and is validated against in situ soil moisture data from the OZnet soil moisture monitoring network, in South-Eastern Australia. 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| subjects | Applied geophysics Downscaling algorithm Earth sciences Earth, ocean, space Enginyeria de la telecomunicació Exact sciences and technology Internal geophysics Joining processes Mesurament Microones Microwave measurements MODIS passive microwave remote sensing Radiocomunicació i exploració electromagnètica Satellites Satèl·lits i ràdioenllaços Sistemes d'informació geogràfica SMOS Soil moisture Spatial resolution Vegetation mapping Àrees temàtiques de la UPC |
| title | Downscaling SMOS-Derived Soil Moisture Using MODIS Visible/Infrared Data |
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