Calibrating the impact of root orientation on root quantification using ground-penetrating radar
BACKGROUND AND AIMS: Ground-penetrating radar (GPR) has provided a non-invasive means for field root investigation. However, the horizontal cross angle (x) of root orientation intersecting a survey line considerably impacts the amplitude area (A) reflected from a root and impairs the accuracy of GPR...
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description | BACKGROUND AND AIMS: Ground-penetrating radar (GPR) has provided a non-invasive means for field root investigation. However, the horizontal cross angle (x) of root orientation intersecting a survey line considerably impacts the amplitude area (A) reflected from a root and impairs the accuracy of GPR-based root quantification. Prediction of A(90°) (the value of A scanning at x = 90°) from multiple A(x) measurements could correct such impact. Previous method of A(90°) prediction focused on target roots at field point scale. The aim of this study is to develop a method to predict A(90°) at field plot scale. METHODS: A(90°) was predicted by a pair of A(x) measured at two arbitrary scanning lines together with an estimated soil background amplitude area. Three independent datasets were employed to test the proposed method. The field experiment included radar data collected for six roots of Caragana microphylla in a sandy-clay soil at four cross angles (30°, 45°, 60°, and 90°). The sand box experiment included radar data for 12 dowels at 13 cross angles (0° to 180°, in 15° steps). The simulation experiment included A(x) of 46 simulated roots at 13 cross angles (0° to 180°, in 15° steps). RESULTS: For all experiments, A(90°) was accurately estimated. Root orientation could also be determined. After correcting the impact of cross angle, the accuracy of root diameter estimation improved. Correlation coefficient between actual and estimated root diameters increased from 0.77 to 0.81, with RMSE declining from 9.53 to 7.05 mm. CONCLUSIONS: A method of correcting the influence of root orientation on root GPR signal at the field plot scale has been established. This method enhances root quantification using GPR. |
doi_str_mv | 10.1007/s11104-015-2563-9 |
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However, the horizontal cross angle (x) of root orientation intersecting a survey line considerably impacts the amplitude area (A) reflected from a root and impairs the accuracy of GPR-based root quantification. Prediction of A(90°) (the value of A scanning at x = 90°) from multiple A(x) measurements could correct such impact. Previous method of A(90°) prediction focused on target roots at field point scale. The aim of this study is to develop a method to predict A(90°) at field plot scale. METHODS: A(90°) was predicted by a pair of A(x) measured at two arbitrary scanning lines together with an estimated soil background amplitude area. Three independent datasets were employed to test the proposed method. The field experiment included radar data collected for six roots of Caragana microphylla in a sandy-clay soil at four cross angles (30°, 45°, 60°, and 90°). The sand box experiment included radar data for 12 dowels at 13 cross angles (0° to 180°, in 15° steps). The simulation experiment included A(x) of 46 simulated roots at 13 cross angles (0° to 180°, in 15° steps). RESULTS: For all experiments, A(90°) was accurately estimated. Root orientation could also be determined. After correcting the impact of cross angle, the accuracy of root diameter estimation improved. Correlation coefficient between actual and estimated root diameters increased from 0.77 to 0.81, with RMSE declining from 9.53 to 7.05 mm. CONCLUSIONS: A method of correcting the influence of root orientation on root GPR signal at the field plot scale has been established. This method enhances root quantification using GPR.</description><identifier>ISSN: 0032-079X</identifier><identifier>EISSN: 1573-5036</identifier><identifier>DOI: 10.1007/s11104-015-2563-9</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Biomass ; Biomedical and Life Sciences ; Caragana ; Caragana microphylla ; Charcoal ; Correlation coefficient ; data collection ; Ecology ; field experimentation ; Flowers & plants ; Ground penetrating radar ; Life Sciences ; Observations ; Plant Physiology ; Plant Sciences ; Plant-soil relationships ; prediction ; Radar ; Radar systems ; Regular Article ; Roots ; sand ; sandy clay soils ; Soil Science & Conservation ; Soils ; surveys</subject><ispartof>Plant and soil, 2015-10, Vol.395 (1-2), p.289-305</ispartof><rights>Springer Science+Business Media 2015</rights><rights>Springer International Publishing Switzerland 2015</rights><rights>COPYRIGHT 2015 Springer</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c570t-259d565191a550a6e5b2b59f6e57c548c963a99ea0dd3b66e6461cca375b7f2d3</citedby><cites>FETCH-LOGICAL-c570t-259d565191a550a6e5b2b59f6e57c548c963a99ea0dd3b66e6461cca375b7f2d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/43872476$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/43872476$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,780,784,803,27924,27925,41488,42557,51319,58017,58250</link.rule.ids></links><search><creatorcontrib>Guo, Li</creatorcontrib><creatorcontrib>Wu, Yuan</creatorcontrib><creatorcontrib>Chen, Jin</creatorcontrib><creatorcontrib>Hirano, Yasuhiro</creatorcontrib><creatorcontrib>Tanikawa, Toko</creatorcontrib><creatorcontrib>Li, Wentao</creatorcontrib><creatorcontrib>Cui, Xihong</creatorcontrib><title>Calibrating the impact of root orientation on root quantification using ground-penetrating radar</title><title>Plant and soil</title><addtitle>Plant Soil</addtitle><description>BACKGROUND AND AIMS: Ground-penetrating radar (GPR) has provided a non-invasive means for field root investigation. However, the horizontal cross angle (x) of root orientation intersecting a survey line considerably impacts the amplitude area (A) reflected from a root and impairs the accuracy of GPR-based root quantification. Prediction of A(90°) (the value of A scanning at x = 90°) from multiple A(x) measurements could correct such impact. Previous method of A(90°) prediction focused on target roots at field point scale. The aim of this study is to develop a method to predict A(90°) at field plot scale. METHODS: A(90°) was predicted by a pair of A(x) measured at two arbitrary scanning lines together with an estimated soil background amplitude area. Three independent datasets were employed to test the proposed method. The field experiment included radar data collected for six roots of Caragana microphylla in a sandy-clay soil at four cross angles (30°, 45°, 60°, and 90°). The sand box experiment included radar data for 12 dowels at 13 cross angles (0° to 180°, in 15° steps). The simulation experiment included A(x) of 46 simulated roots at 13 cross angles (0° to 180°, in 15° steps). RESULTS: For all experiments, A(90°) was accurately estimated. Root orientation could also be determined. After correcting the impact of cross angle, the accuracy of root diameter estimation improved. Correlation coefficient between actual and estimated root diameters increased from 0.77 to 0.81, with RMSE declining from 9.53 to 7.05 mm. CONCLUSIONS: A method of correcting the influence of root orientation on root GPR signal at the field plot scale has been established. This method enhances root quantification using GPR.</description><subject>Biomass</subject><subject>Biomedical and Life Sciences</subject><subject>Caragana</subject><subject>Caragana microphylla</subject><subject>Charcoal</subject><subject>Correlation coefficient</subject><subject>data collection</subject><subject>Ecology</subject><subject>field experimentation</subject><subject>Flowers & plants</subject><subject>Ground penetrating radar</subject><subject>Life Sciences</subject><subject>Observations</subject><subject>Plant Physiology</subject><subject>Plant Sciences</subject><subject>Plant-soil relationships</subject><subject>prediction</subject><subject>Radar</subject><subject>Radar systems</subject><subject>Regular Article</subject><subject>Roots</subject><subject>sand</subject><subject>sandy clay soils</subject><subject>Soil Science & Conservation</subject><subject>Soils</subject><subject>surveys</subject><issn>0032-079X</issn><issn>1573-5036</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9UcGOFCEQ7RhNHFc_wIOxEy9eei2ggea4mazuJpt40E28IU1Dy6QHZoE--PfW2BtjPBhICqree1TxmuY1gUsCID8UQgj0HRDeUS5Yp540O8Il6zgw8bTZATDagVTfnjcvSjnA-U7Ervm-N0sYs6khzm394dpwPBlb2-TbnBLGHFysWE6xxf0797CaWIMPdkuv5cydc1rj1J1cdPVRLpvJ5JfNM2-W4l49xovm_uP11_1Nd_f50-3-6q6zXELFptXEBSeKGM7BCMdHOnLl8SAt7werBDNKOQPTxEYhnOgFsdYwyUfp6cQumveb7imnh9WVqo-hWLcsJrq0Fk0kpWRgtJcIffcP9JDWHLE7RJGecwYSEHW5oWazOB2iTziXxTW5Y7ApOh8wf9VTxQXlA0cC2Qg2p1Ky8_qUw9Hkn5qAPpukN5M0mqTPJmmFHLpxCmLj7PJfrfyH9GYjHUpN-c8rPRskjiew_nare5O0mXMo-v4LRQEA_AMYGPsFglmnMg</recordid><startdate>20151001</startdate><enddate>20151001</enddate><creator>Guo, Li</creator><creator>Wu, Yuan</creator><creator>Chen, Jin</creator><creator>Hirano, Yasuhiro</creator><creator>Tanikawa, Toko</creator><creator>Li, Wentao</creator><creator>Cui, Xihong</creator><general>Springer International Publishing</general><general>Springer</general><general>Springer Nature B.V</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SN</scope><scope>7ST</scope><scope>7T7</scope><scope>7X2</scope><scope>88A</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M0K</scope><scope>M7P</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>RC3</scope><scope>SOI</scope></search><sort><creationdate>20151001</creationdate><title>Calibrating the impact of root orientation on root quantification using ground-penetrating radar</title><author>Guo, Li ; Wu, Yuan ; Chen, Jin ; Hirano, Yasuhiro ; Tanikawa, Toko ; Li, Wentao ; Cui, Xihong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c570t-259d565191a550a6e5b2b59f6e57c548c963a99ea0dd3b66e6461cca375b7f2d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Biomass</topic><topic>Biomedical and Life Sciences</topic><topic>Caragana</topic><topic>Caragana microphylla</topic><topic>Charcoal</topic><topic>Correlation coefficient</topic><topic>data collection</topic><topic>Ecology</topic><topic>field experimentation</topic><topic>Flowers & plants</topic><topic>Ground penetrating radar</topic><topic>Life Sciences</topic><topic>Observations</topic><topic>Plant Physiology</topic><topic>Plant Sciences</topic><topic>Plant-soil relationships</topic><topic>prediction</topic><topic>Radar</topic><topic>Radar systems</topic><topic>Regular Article</topic><topic>Roots</topic><topic>sand</topic><topic>sandy clay soils</topic><topic>Soil Science & Conservation</topic><topic>Soils</topic><topic>surveys</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guo, Li</creatorcontrib><creatorcontrib>Wu, Yuan</creatorcontrib><creatorcontrib>Chen, Jin</creatorcontrib><creatorcontrib>Hirano, Yasuhiro</creatorcontrib><creatorcontrib>Tanikawa, Toko</creatorcontrib><creatorcontrib>Li, Wentao</creatorcontrib><creatorcontrib>Cui, Xihong</creatorcontrib><collection>AGRIS</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Agricultural Science Collection</collection><collection>Biology Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Genetics Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Plant and soil</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guo, Li</au><au>Wu, Yuan</au><au>Chen, Jin</au><au>Hirano, Yasuhiro</au><au>Tanikawa, Toko</au><au>Li, Wentao</au><au>Cui, Xihong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Calibrating the impact of root orientation on root quantification using ground-penetrating radar</atitle><jtitle>Plant and soil</jtitle><stitle>Plant Soil</stitle><date>2015-10-01</date><risdate>2015</risdate><volume>395</volume><issue>1-2</issue><spage>289</spage><epage>305</epage><pages>289-305</pages><issn>0032-079X</issn><eissn>1573-5036</eissn><abstract>BACKGROUND AND AIMS: Ground-penetrating radar (GPR) has provided a non-invasive means for field root investigation. However, the horizontal cross angle (x) of root orientation intersecting a survey line considerably impacts the amplitude area (A) reflected from a root and impairs the accuracy of GPR-based root quantification. Prediction of A(90°) (the value of A scanning at x = 90°) from multiple A(x) measurements could correct such impact. Previous method of A(90°) prediction focused on target roots at field point scale. The aim of this study is to develop a method to predict A(90°) at field plot scale. METHODS: A(90°) was predicted by a pair of A(x) measured at two arbitrary scanning lines together with an estimated soil background amplitude area. Three independent datasets were employed to test the proposed method. The field experiment included radar data collected for six roots of Caragana microphylla in a sandy-clay soil at four cross angles (30°, 45°, 60°, and 90°). The sand box experiment included radar data for 12 dowels at 13 cross angles (0° to 180°, in 15° steps). The simulation experiment included A(x) of 46 simulated roots at 13 cross angles (0° to 180°, in 15° steps). RESULTS: For all experiments, A(90°) was accurately estimated. Root orientation could also be determined. After correcting the impact of cross angle, the accuracy of root diameter estimation improved. Correlation coefficient between actual and estimated root diameters increased from 0.77 to 0.81, with RMSE declining from 9.53 to 7.05 mm. CONCLUSIONS: A method of correcting the influence of root orientation on root GPR signal at the field plot scale has been established. This method enhances root quantification using GPR.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s11104-015-2563-9</doi><tpages>17</tpages></addata></record> |
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subjects | Biomass Biomedical and Life Sciences Caragana Caragana microphylla Charcoal Correlation coefficient data collection Ecology field experimentation Flowers & plants Ground penetrating radar Life Sciences Observations Plant Physiology Plant Sciences Plant-soil relationships prediction Radar Radar systems Regular Article Roots sand sandy clay soils Soil Science & Conservation Soils surveys |
title | Calibrating the impact of root orientation on root quantification using ground-penetrating radar |
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