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A comparison of soil moisture retrieval models using SIR-C measurements over the little Washita River watershed
SIR-C L-band measurements over the Little Washita River watershed in Chickasha, Oklahama during 11–17 April 1994 have been analyzed for studying the change of soil moisture in the region. Two algorithms developed recently for estimation of moisture content in bare soil were applied to these measurem...
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Published in: | Remote sensing of environment 1997-02, Vol.59 (2), p.308-320 |
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description | SIR-C L-band measurements over the Little Washita River watershed in Chickasha, Oklahama during 11–17 April 1994 have been analyzed for studying the change of soil moisture in the region. Two algorithms developed recently for estimation of moisture content in bare soil were applied to these measurements and the results were compared with those sampled on the ground. There is a good agreement between the values of soil moisture estimated by either one of the algorithms and those measured from ground sampling for bare or sparsely vegetated fields. The standard error from this comparison is on the order of 0.05–0.06 cm
3/cm
3, which is comparable to that expected from a regression between backscattering coefficients and measured soil moisture. Both algorithms provide a poor estimation of soil moisture or fail to give solutions to areas covered with moderate or dense vegetation. Even for bare soils the number of pixels that bear no numerical solution from the application of either one of the two algorithms to the data is not negligible. Results from using one of these algorithms indicate that the fraction of these pixels becomes larger as the bare soils become drier. The other algorithm generally gives a larger fraction of these pixels when the fields are vegetation-covered. The implication and impact of these features are discussed in this article. |
doi_str_mv | 10.1016/S0034-4257(96)00145-9 |
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3/cm
3, which is comparable to that expected from a regression between backscattering coefficients and measured soil moisture. Both algorithms provide a poor estimation of soil moisture or fail to give solutions to areas covered with moderate or dense vegetation. Even for bare soils the number of pixels that bear no numerical solution from the application of either one of the two algorithms to the data is not negligible. Results from using one of these algorithms indicate that the fraction of these pixels becomes larger as the bare soils become drier. The other algorithm generally gives a larger fraction of these pixels when the fields are vegetation-covered. The implication and impact of these features are discussed in this article.</description><identifier>ISSN: 0034-4257</identifier><identifier>EISSN: 1879-0704</identifier><identifier>DOI: 10.1016/S0034-4257(96)00145-9</identifier><language>eng</language><publisher>Elsevier Inc</publisher><subject>Algorithms ; CONTENIDO DE AGUA EN EL SUELO ; Electromagnetic wave backscattering ; Errors ; MATEMATICAS ; MATHEMATICAL MODELS ; MATHEMATICS ; MATHEMATIQUE ; MODELE MATHEMATIQUE ; MODELOS MATEMATICOS ; Moisture determination ; OKLAHOMA ; Regression analysis ; Rivers ; SOIL WATER CONTENT ; Soils ; SPACE SHUTTLE IMAGING RADAR-C ; TENEUR EN EAU DU SOL ; Watersheds</subject><ispartof>Remote sensing of environment, 1997-02, Vol.59 (2), p.308-320</ispartof><rights>1997</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c352t-2bc86e08665601824ce6f39ce261e6e3a713f58c51a729c6452a3f022de04ef13</citedby><cites>FETCH-LOGICAL-c352t-2bc86e08665601824ce6f39ce261e6e3a713f58c51a729c6452a3f022de04ef13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Wang, J.R.</creatorcontrib><creatorcontrib>Hsu, A.</creatorcontrib><creatorcontrib>Shi, J.C.</creatorcontrib><creatorcontrib>O'Neill, P.E.</creatorcontrib><creatorcontrib>Engman, E.T.</creatorcontrib><title>A comparison of soil moisture retrieval models using SIR-C measurements over the little Washita River watershed</title><title>Remote sensing of environment</title><description>SIR-C L-band measurements over the Little Washita River watershed in Chickasha, Oklahama during 11–17 April 1994 have been analyzed for studying the change of soil moisture in the region. Two algorithms developed recently for estimation of moisture content in bare soil were applied to these measurements and the results were compared with those sampled on the ground. There is a good agreement between the values of soil moisture estimated by either one of the algorithms and those measured from ground sampling for bare or sparsely vegetated fields. The standard error from this comparison is on the order of 0.05–0.06 cm
3/cm
3, which is comparable to that expected from a regression between backscattering coefficients and measured soil moisture. Both algorithms provide a poor estimation of soil moisture or fail to give solutions to areas covered with moderate or dense vegetation. Even for bare soils the number of pixels that bear no numerical solution from the application of either one of the two algorithms to the data is not negligible. Results from using one of these algorithms indicate that the fraction of these pixels becomes larger as the bare soils become drier. The other algorithm generally gives a larger fraction of these pixels when the fields are vegetation-covered. The implication and impact of these features are discussed in this article.</description><subject>Algorithms</subject><subject>CONTENIDO DE AGUA EN EL SUELO</subject><subject>Electromagnetic wave backscattering</subject><subject>Errors</subject><subject>MATEMATICAS</subject><subject>MATHEMATICAL MODELS</subject><subject>MATHEMATICS</subject><subject>MATHEMATIQUE</subject><subject>MODELE MATHEMATIQUE</subject><subject>MODELOS MATEMATICOS</subject><subject>Moisture determination</subject><subject>OKLAHOMA</subject><subject>Regression analysis</subject><subject>Rivers</subject><subject>SOIL WATER CONTENT</subject><subject>Soils</subject><subject>SPACE SHUTTLE IMAGING RADAR-C</subject><subject>TENEUR EN EAU DU SOL</subject><subject>Watersheds</subject><issn>0034-4257</issn><issn>1879-0704</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1997</creationdate><recordtype>article</recordtype><recordid>eNqFkUtrFEEUhQtRcBz9A4JQKx-LTupdXSsJg49AIJAxuCzK6tuZku6usW7NiP_e7oy4TFYX7vnO2XyEvOHsjDNuzreMSdUooe17Zz4wxpVu3BOy4q11DbNMPSWr_8hz8gLx5wzp1vIVyRc05nEfSsI80dxTzGmgY05YDwVogVoSHMPy6mBAesA03dHt5U2zoSMEnKERpoo0H6HQugM6pFoHoN8D7lIN9CYtwe9QoeAOupfkWR8GhFf_7prcfv70bfO1ubr-crm5uGqi1KI24kdsDbDWGG0Yb4WKYHrpIgjDwYAMlstet1HzYIWLRmkRZM-E6IAp6Llck3en3X3Jvw6A1Y8JIwxDmCAf0FulrTKGL-TbB0lhlJXSPA5y7azTM7wm-gTGkhEL9H5f0hjKH8-ZX4z5e2N-0eGd8ffGvJt7r0-9PmQf7mYl_nbrLHdMizn8eApnC3BMUDzGBFOELhWI1Xc5PTL_FwtYpeI</recordid><startdate>19970201</startdate><enddate>19970201</enddate><creator>Wang, J.R.</creator><creator>Hsu, A.</creator><creator>Shi, J.C.</creator><creator>O'Neill, P.E.</creator><creator>Engman, E.T.</creator><general>Elsevier Inc</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7UA</scope><scope>C1K</scope><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope><scope>7TC</scope></search><sort><creationdate>19970201</creationdate><title>A comparison of soil moisture retrieval models using SIR-C measurements over the little Washita River watershed</title><author>Wang, J.R. ; Hsu, A. ; Shi, J.C. ; O'Neill, P.E. ; Engman, E.T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c352t-2bc86e08665601824ce6f39ce261e6e3a713f58c51a729c6452a3f022de04ef13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1997</creationdate><topic>Algorithms</topic><topic>CONTENIDO DE AGUA EN EL SUELO</topic><topic>Electromagnetic wave backscattering</topic><topic>Errors</topic><topic>MATEMATICAS</topic><topic>MATHEMATICAL MODELS</topic><topic>MATHEMATICS</topic><topic>MATHEMATIQUE</topic><topic>MODELE MATHEMATIQUE</topic><topic>MODELOS MATEMATICOS</topic><topic>Moisture determination</topic><topic>OKLAHOMA</topic><topic>Regression analysis</topic><topic>Rivers</topic><topic>SOIL WATER CONTENT</topic><topic>Soils</topic><topic>SPACE SHUTTLE IMAGING RADAR-C</topic><topic>TENEUR EN EAU DU SOL</topic><topic>Watersheds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, J.R.</creatorcontrib><creatorcontrib>Hsu, A.</creatorcontrib><creatorcontrib>Shi, J.C.</creatorcontrib><creatorcontrib>O'Neill, P.E.</creatorcontrib><creatorcontrib>Engman, E.T.</creatorcontrib><collection>AGRIS</collection><collection>CrossRef</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Mechanical Engineering Abstracts</collection><jtitle>Remote sensing of environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, J.R.</au><au>Hsu, A.</au><au>Shi, J.C.</au><au>O'Neill, P.E.</au><au>Engman, E.T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A comparison of soil moisture retrieval models using SIR-C measurements over the little Washita River watershed</atitle><jtitle>Remote sensing of environment</jtitle><date>1997-02-01</date><risdate>1997</risdate><volume>59</volume><issue>2</issue><spage>308</spage><epage>320</epage><pages>308-320</pages><issn>0034-4257</issn><eissn>1879-0704</eissn><abstract>SIR-C L-band measurements over the Little Washita River watershed in Chickasha, Oklahama during 11–17 April 1994 have been analyzed for studying the change of soil moisture in the region. Two algorithms developed recently for estimation of moisture content in bare soil were applied to these measurements and the results were compared with those sampled on the ground. There is a good agreement between the values of soil moisture estimated by either one of the algorithms and those measured from ground sampling for bare or sparsely vegetated fields. The standard error from this comparison is on the order of 0.05–0.06 cm
3/cm
3, which is comparable to that expected from a regression between backscattering coefficients and measured soil moisture. Both algorithms provide a poor estimation of soil moisture or fail to give solutions to areas covered with moderate or dense vegetation. Even for bare soils the number of pixels that bear no numerical solution from the application of either one of the two algorithms to the data is not negligible. Results from using one of these algorithms indicate that the fraction of these pixels becomes larger as the bare soils become drier. The other algorithm generally gives a larger fraction of these pixels when the fields are vegetation-covered. The implication and impact of these features are discussed in this article.</abstract><pub>Elsevier Inc</pub><doi>10.1016/S0034-4257(96)00145-9</doi><tpages>13</tpages></addata></record> |
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subjects | Algorithms CONTENIDO DE AGUA EN EL SUELO Electromagnetic wave backscattering Errors MATEMATICAS MATHEMATICAL MODELS MATHEMATICS MATHEMATIQUE MODELE MATHEMATIQUE MODELOS MATEMATICOS Moisture determination OKLAHOMA Regression analysis Rivers SOIL WATER CONTENT Soils SPACE SHUTTLE IMAGING RADAR-C TENEUR EN EAU DU SOL Watersheds |
title | A comparison of soil moisture retrieval models using SIR-C measurements over the little Washita River watershed |
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