ScatSat-1 Leaf Area Index Product: Models Comparison, Development, and Validation Over Cropland
The leaf area index (LAI) is a crucial parameter that governs the physical and biophysical processes of plant canopies and acts as an input variable in land surface and soil moisture modeling. The ScatSat-1 is the latest microwave Ku-band scatterometer mission of Indian Space Research Organization (...
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creator | Singh, Ujjwal Srivastava, Prashant K. Pandey, Dharmendra Kumar Chaurasia, Sasmita Gupta, Dileep Kumar Chaudhary, Sumit Kumar Prasad, Rajendra Raghubanshi, A. S. |
description | The leaf area index (LAI) is a crucial parameter that governs the physical and biophysical processes of plant canopies and acts as an input variable in land surface and soil moisture modeling. The ScatSat-1 is the latest microwave Ku-band scatterometer mission of Indian Space Research Organization (ISRO), provides data at a higher temporal and spatial resolution for various applications. Due to its all-weather operational capability, it could be used as an alternative to the optical/IR sensors for the LAI estimation. In the technical literature domain, no testing has been done to estimate the LAI using ScatSat-1 scatterometer data. Therefore, the objective of this study is to retrieve the LAI using the ScatSat-1 backscattering by modifications of two different models viz. water cloud model (WCM) and the recently developed Oveisgharan et al. model and compared against the PROBA-V, MODIS, and ground-based LAI products. To assess the performance of these models, coefficient of determination ( R^{2} ), root-mean-squared error (RMSE) and bias are computed. For Oveisgharan et al. , the values of R^{2} , RMSE and bias were obtained as 0.87, 0.57 m 2 m −2 , and 0.05 m 2 m −2 respectively, whereas for WCM model, the values were found as 0.82, 0.67 m 2 m −2 , and 0.32 m 2 m −2 respectively. This investigation showed that the modifications in Oveisgharan et al. model provide marginally better results in the retrieval of LAI using ScatSat-1 data than the WCM model. The models' limitation may be less serious for crop management studies because the majority of crops attains its maturity at LAI values less than 6 m 2 /m 2 . |
doi_str_mv | 10.1109/LGRS.2019.2927468 |
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S.</creator><creatorcontrib>Singh, Ujjwal ; Srivastava, Prashant K. ; Pandey, Dharmendra Kumar ; Chaurasia, Sasmita ; Gupta, Dileep Kumar ; Chaudhary, Sumit Kumar ; Prasad, Rajendra ; Raghubanshi, A. S.</creatorcontrib><description><![CDATA[The leaf area index (LAI) is a crucial parameter that governs the physical and biophysical processes of plant canopies and acts as an input variable in land surface and soil moisture modeling. The ScatSat-1 is the latest microwave Ku-band scatterometer mission of Indian Space Research Organization (ISRO), provides data at a higher temporal and spatial resolution for various applications. Due to its all-weather operational capability, it could be used as an alternative to the optical/IR sensors for the LAI estimation. In the technical literature domain, no testing has been done to estimate the LAI using ScatSat-1 scatterometer data. Therefore, the objective of this study is to retrieve the LAI using the ScatSat-1 backscattering by modifications of two different models viz. water cloud model (WCM) and the recently developed Oveisgharan et al. model and compared against the PROBA-V, MODIS, and ground-based LAI products. To assess the performance of these models, coefficient of determination (<inline-formula> <tex-math notation="LaTeX">R^{2} </tex-math></inline-formula>), root-mean-squared error (RMSE) and bias are computed. For Oveisgharan et al. , the values of <inline-formula> <tex-math notation="LaTeX">R^{2} </tex-math></inline-formula>, RMSE and bias were obtained as 0.87, 0.57 m 2 m −2 , and 0.05 m 2 m −2 respectively, whereas for WCM model, the values were found as 0.82, 0.67 m 2 m −2 , and 0.32 m 2 m −2 respectively. This investigation showed that the modifications in Oveisgharan et al. model provide marginally better results in the retrieval of LAI using ScatSat-1 data than the WCM model. The models' limitation may be less serious for crop management studies because the majority of crops attains its maturity at LAI values less than 6 m 2 /m 2 .]]></description><identifier>ISSN: 1545-598X</identifier><identifier>EISSN: 1558-0571</identifier><identifier>DOI: 10.1109/LGRS.2019.2927468</identifier><identifier>CODEN: IGRSBY</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Agricultural land ; Agriculture ; Backscatter ; Backscattering ; Bias ; Computational modeling ; Crop management ; Indexes ; Indian space program ; Leaf area ; Leaf area index ; leaf area index (LAI) ; Leaves ; Oveisgharan <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">et al. ; Root-mean-square errors ; ScatSat-1 ; Scatterometers ; Sea measurements ; Soil ; Soil moisture ; Space research ; Spatial discrimination ; Spatial resolution ; Synthetic aperture radar ; Technical literature ; Vegetation mapping ; water cloud model (WCM) ; Weather</subject><ispartof>IEEE geoscience and remote sensing letters, 2020-04, Vol.17 (4), p.563-567</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-2bfcabef40d12b36a3dd3de133a624e4383bf9d8ac1e9086e0df3fa7347844563</citedby><cites>FETCH-LOGICAL-c293t-2bfcabef40d12b36a3dd3de133a624e4383bf9d8ac1e9086e0df3fa7347844563</cites><orcidid>0000-0002-4155-630X ; 0000-0001-6553-0983 ; 0000-0001-7475-6482 ; 0000-0002-9325-4653 ; 0000-0002-4060-5368</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8798752$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,777,781,793,27905,27906,54739</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8798752$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Singh, Ujjwal</creatorcontrib><creatorcontrib>Srivastava, Prashant K.</creatorcontrib><creatorcontrib>Pandey, Dharmendra Kumar</creatorcontrib><creatorcontrib>Chaurasia, Sasmita</creatorcontrib><creatorcontrib>Gupta, Dileep Kumar</creatorcontrib><creatorcontrib>Chaudhary, Sumit Kumar</creatorcontrib><creatorcontrib>Prasad, Rajendra</creatorcontrib><creatorcontrib>Raghubanshi, A. S.</creatorcontrib><title>ScatSat-1 Leaf Area Index Product: Models Comparison, Development, and Validation Over Cropland</title><title>IEEE geoscience and remote sensing letters</title><addtitle>LGRS</addtitle><description><![CDATA[The leaf area index (LAI) is a crucial parameter that governs the physical and biophysical processes of plant canopies and acts as an input variable in land surface and soil moisture modeling. The ScatSat-1 is the latest microwave Ku-band scatterometer mission of Indian Space Research Organization (ISRO), provides data at a higher temporal and spatial resolution for various applications. Due to its all-weather operational capability, it could be used as an alternative to the optical/IR sensors for the LAI estimation. In the technical literature domain, no testing has been done to estimate the LAI using ScatSat-1 scatterometer data. Therefore, the objective of this study is to retrieve the LAI using the ScatSat-1 backscattering by modifications of two different models viz. water cloud model (WCM) and the recently developed Oveisgharan et al. model and compared against the PROBA-V, MODIS, and ground-based LAI products. To assess the performance of these models, coefficient of determination (<inline-formula> <tex-math notation="LaTeX">R^{2} </tex-math></inline-formula>), root-mean-squared error (RMSE) and bias are computed. For Oveisgharan et al. , the values of <inline-formula> <tex-math notation="LaTeX">R^{2} </tex-math></inline-formula>, RMSE and bias were obtained as 0.87, 0.57 m 2 m −2 , and 0.05 m 2 m −2 respectively, whereas for WCM model, the values were found as 0.82, 0.67 m 2 m −2 , and 0.32 m 2 m −2 respectively. This investigation showed that the modifications in Oveisgharan et al. model provide marginally better results in the retrieval of LAI using ScatSat-1 data than the WCM model. The models' limitation may be less serious for crop management studies because the majority of crops attains its maturity at LAI values less than 6 m 2 /m 2 .]]></description><subject>Agricultural land</subject><subject>Agriculture</subject><subject>Backscatter</subject><subject>Backscattering</subject><subject>Bias</subject><subject>Computational modeling</subject><subject>Crop management</subject><subject>Indexes</subject><subject>Indian space program</subject><subject>Leaf area</subject><subject>Leaf area index</subject><subject>leaf area index (LAI)</subject><subject>Leaves</subject><subject>Oveisgharan <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">et al.</subject><subject>Root-mean-square errors</subject><subject>ScatSat-1</subject><subject>Scatterometers</subject><subject>Sea measurements</subject><subject>Soil</subject><subject>Soil moisture</subject><subject>Space research</subject><subject>Spatial discrimination</subject><subject>Spatial resolution</subject><subject>Synthetic aperture radar</subject><subject>Technical literature</subject><subject>Vegetation mapping</subject><subject>water cloud model (WCM)</subject><subject>Weather</subject><issn>1545-598X</issn><issn>1558-0571</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kF1LwzAUhoMoOKc_QLwJeLvOfLVJvRtT56AycSrehbQ5hY6uqUk39N_bsuHVeeE87znwIHRNyZRSkt5li7f1lBGaTlnKpEjUCRrROFYRiSU9HbKIozhVX-foIoQNIUwoJUdIrwvTrU0XUZyBKfHMg8HLxsIPfvXO7oruHr84C3XAc7dtja-Cayb4AfZQu3YLTTfBprH409SVNV3lGrzag8dz79q6X1yis9LUAa6Oc4w-nh7f589Rtlos57MsKljKu4jlZWFyKAWxlOU8MdxaboFybhImQHDF8zK1yhQUUqISILbkpZFcSCVEnPAxuj3cbb373kHo9MbtfNO_1Kwvc6aolD1FD1ThXQgeSt36amv8r6ZEDx714FEPHvXRY9-5OXQqAPjnlUyVjBn_A7m0bm8</recordid><startdate>20200401</startdate><enddate>20200401</enddate><creator>Singh, Ujjwal</creator><creator>Srivastava, Prashant K.</creator><creator>Pandey, Dharmendra Kumar</creator><creator>Chaurasia, Sasmita</creator><creator>Gupta, Dileep Kumar</creator><creator>Chaudhary, Sumit Kumar</creator><creator>Prasad, Rajendra</creator><creator>Raghubanshi, A. S.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>JQ2</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-4155-630X</orcidid><orcidid>https://orcid.org/0000-0001-6553-0983</orcidid><orcidid>https://orcid.org/0000-0001-7475-6482</orcidid><orcidid>https://orcid.org/0000-0002-9325-4653</orcidid><orcidid>https://orcid.org/0000-0002-4060-5368</orcidid></search><sort><creationdate>20200401</creationdate><title>ScatSat-1 Leaf Area Index Product: Models Comparison, Development, and Validation Over Cropland</title><author>Singh, Ujjwal ; Srivastava, Prashant K. ; Pandey, Dharmendra Kumar ; Chaurasia, Sasmita ; Gupta, Dileep Kumar ; Chaudhary, Sumit Kumar ; Prasad, Rajendra ; Raghubanshi, A. 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S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>ScatSat-1 Leaf Area Index Product: Models Comparison, Development, and Validation Over Cropland</atitle><jtitle>IEEE geoscience and remote sensing letters</jtitle><stitle>LGRS</stitle><date>2020-04-01</date><risdate>2020</risdate><volume>17</volume><issue>4</issue><spage>563</spage><epage>567</epage><pages>563-567</pages><issn>1545-598X</issn><eissn>1558-0571</eissn><coden>IGRSBY</coden><abstract><![CDATA[The leaf area index (LAI) is a crucial parameter that governs the physical and biophysical processes of plant canopies and acts as an input variable in land surface and soil moisture modeling. The ScatSat-1 is the latest microwave Ku-band scatterometer mission of Indian Space Research Organization (ISRO), provides data at a higher temporal and spatial resolution for various applications. Due to its all-weather operational capability, it could be used as an alternative to the optical/IR sensors for the LAI estimation. In the technical literature domain, no testing has been done to estimate the LAI using ScatSat-1 scatterometer data. Therefore, the objective of this study is to retrieve the LAI using the ScatSat-1 backscattering by modifications of two different models viz. water cloud model (WCM) and the recently developed Oveisgharan et al. model and compared against the PROBA-V, MODIS, and ground-based LAI products. To assess the performance of these models, coefficient of determination (<inline-formula> <tex-math notation="LaTeX">R^{2} </tex-math></inline-formula>), root-mean-squared error (RMSE) and bias are computed. For Oveisgharan et al. , the values of <inline-formula> <tex-math notation="LaTeX">R^{2} </tex-math></inline-formula>, RMSE and bias were obtained as 0.87, 0.57 m 2 m −2 , and 0.05 m 2 m −2 respectively, whereas for WCM model, the values were found as 0.82, 0.67 m 2 m −2 , and 0.32 m 2 m −2 respectively. This investigation showed that the modifications in Oveisgharan et al. model provide marginally better results in the retrieval of LAI using ScatSat-1 data than the WCM model. The models' limitation may be less serious for crop management studies because the majority of crops attains its maturity at LAI values less than 6 m 2 /m 2 .]]></abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/LGRS.2019.2927468</doi><tpages>5</tpages><orcidid>https://orcid.org/0000-0002-4155-630X</orcidid><orcidid>https://orcid.org/0000-0001-6553-0983</orcidid><orcidid>https://orcid.org/0000-0001-7475-6482</orcidid><orcidid>https://orcid.org/0000-0002-9325-4653</orcidid><orcidid>https://orcid.org/0000-0002-4060-5368</orcidid></addata></record> |
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subjects | Agricultural land Agriculture Backscatter Backscattering Bias Computational modeling Crop management Indexes Indian space program Leaf area Leaf area index leaf area index (LAI) Leaves Oveisgharan <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">et al. Root-mean-square errors ScatSat-1 Scatterometers Sea measurements Soil Soil moisture Space research Spatial discrimination Spatial resolution Synthetic aperture radar Technical literature Vegetation mapping water cloud model (WCM) Weather |
title | ScatSat-1 Leaf Area Index Product: Models Comparison, Development, and Validation Over Cropland |
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