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Scattering Intensity Analysis and Classification of Two Types of Rice Based on Multi-Temporal and Multi-Mode Simulated Compact Polarimetric SAR Data
Because transmitting polarization can be an arbitrary elliptical wave, and theoretically, there are numerous possibilities of hybrid dual-pol modes, therefore, it is necessary to explore the feature recognition and classification ability of compact polarimetric (CP) parameters under different transm...
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Published in: | Remote sensing (Basel, Switzerland) Switzerland), 2022-04, Vol.14 (7), p.1644 |
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description | Because transmitting polarization can be an arbitrary elliptical wave, and theoretically, there are numerous possibilities of hybrid dual-pol modes, therefore, it is necessary to explore the feature recognition and classification ability of compact polarimetric (CP) parameters under different transmitting and receiving modes to different ground objects. In this paper, we first simulated, extracted, and analyzed the scattering intensity of two types of rice of six temporal CP synthetic aperture radar (SAR) data under three transmitting modes. Then, during different phenology stages, the optimal parameters for distinguishing transplanting hybrid rice (T–H) and direct-sown japonica rice (D–J) were acquired. Finally, a decision tree classification model was established based on the optimal parameters to carry out the fine classification of the two types of rice and to verify the results. The results showed that this strategy can obtain a high classification accuracy for the two types of rice with an overall classification accuracy of more than 95% and a kappa coefficient of more than 0.94. In addition, and importantly, we found that the CP parameters in the 1103 period (harvest stage) were the best CP parameters to distinguish the two types of rice, followed by the 0730 (seedling–elongation stage), 0612 (seedling stage), and 0916 (heading–flowering stage) periods. |
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In this paper, we first simulated, extracted, and analyzed the scattering intensity of two types of rice of six temporal CP synthetic aperture radar (SAR) data under three transmitting modes. Then, during different phenology stages, the optimal parameters for distinguishing transplanting hybrid rice (T–H) and direct-sown japonica rice (D–J) were acquired. Finally, a decision tree classification model was established based on the optimal parameters to carry out the fine classification of the two types of rice and to verify the results. The results showed that this strategy can obtain a high classification accuracy for the two types of rice with an overall classification accuracy of more than 95% and a kappa coefficient of more than 0.94. In addition, and importantly, we found that the CP parameters in the 1103 period (harvest stage) were the best CP parameters to distinguish the two types of rice, followed by the 0730 (seedling–elongation stage), 0612 (seedling stage), and 0916 (heading–flowering stage) periods.</description><identifier>ISSN: 2072-4292</identifier><identifier>EISSN: 2072-4292</identifier><identifier>DOI: 10.3390/rs14071644</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Classification ; compact polarimetric (CP) SAR ; Decision trees ; Elongation ; Feature recognition ; Flowering ; Global positioning systems ; GPS ; multi-mode and classification ; Object recognition ; Parameters ; Phenology ; Polarimetry ; Remote sensing ; Rice ; Scattering ; scattering intensity ; Seedlings ; Synthetic aperture radar ; Transmission</subject><ispartof>Remote sensing (Basel, Switzerland), 2022-04, Vol.14 (7), p.1644</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-1a7b8e7f9774657d90d70cb65394865678903985ec683ba4f3fb39de258248e83</citedby><cites>FETCH-LOGICAL-c291t-1a7b8e7f9774657d90d70cb65394865678903985ec683ba4f3fb39de258248e83</cites><orcidid>0000-0002-0901-0577 ; 0000-0002-5795-9533</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2649091401/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2649091401?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,25732,27903,27904,36991,44569,74872</link.rule.ids></links><search><creatorcontrib>Guo, Xianyu</creatorcontrib><creatorcontrib>Yin, Junjun</creatorcontrib><creatorcontrib>Li, Kun</creatorcontrib><creatorcontrib>Yang, Jian</creatorcontrib><creatorcontrib>Shao, Yun</creatorcontrib><title>Scattering Intensity Analysis and Classification of Two Types of Rice Based on Multi-Temporal and Multi-Mode Simulated Compact Polarimetric SAR Data</title><title>Remote sensing (Basel, Switzerland)</title><description>Because transmitting polarization can be an arbitrary elliptical wave, and theoretically, there are numerous possibilities of hybrid dual-pol modes, therefore, it is necessary to explore the feature recognition and classification ability of compact polarimetric (CP) parameters under different transmitting and receiving modes to different ground objects. In this paper, we first simulated, extracted, and analyzed the scattering intensity of two types of rice of six temporal CP synthetic aperture radar (SAR) data under three transmitting modes. Then, during different phenology stages, the optimal parameters for distinguishing transplanting hybrid rice (T–H) and direct-sown japonica rice (D–J) were acquired. Finally, a decision tree classification model was established based on the optimal parameters to carry out the fine classification of the two types of rice and to verify the results. The results showed that this strategy can obtain a high classification accuracy for the two types of rice with an overall classification accuracy of more than 95% and a kappa coefficient of more than 0.94. In addition, and importantly, we found that the CP parameters in the 1103 period (harvest stage) were the best CP parameters to distinguish the two types of rice, followed by the 0730 (seedling–elongation stage), 0612 (seedling stage), and 0916 (heading–flowering stage) periods.</description><subject>Classification</subject><subject>compact polarimetric (CP) SAR</subject><subject>Decision trees</subject><subject>Elongation</subject><subject>Feature recognition</subject><subject>Flowering</subject><subject>Global positioning systems</subject><subject>GPS</subject><subject>multi-mode and classification</subject><subject>Object recognition</subject><subject>Parameters</subject><subject>Phenology</subject><subject>Polarimetry</subject><subject>Remote sensing</subject><subject>Rice</subject><subject>Scattering</subject><subject>scattering intensity</subject><subject>Seedlings</subject><subject>Synthetic aperture 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Intensity Analysis and Classification of Two Types of Rice Based on Multi-Temporal and Multi-Mode Simulated Compact Polarimetric SAR Data</title><author>Guo, Xianyu ; Yin, Junjun ; Li, Kun ; Yang, Jian ; Shao, Yun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-1a7b8e7f9774657d90d70cb65394865678903985ec683ba4f3fb39de258248e83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Classification</topic><topic>compact polarimetric (CP) SAR</topic><topic>Decision trees</topic><topic>Elongation</topic><topic>Feature recognition</topic><topic>Flowering</topic><topic>Global positioning systems</topic><topic>GPS</topic><topic>multi-mode and classification</topic><topic>Object recognition</topic><topic>Parameters</topic><topic>Phenology</topic><topic>Polarimetry</topic><topic>Remote sensing</topic><topic>Rice</topic><topic>Scattering</topic><topic>scattering 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In this paper, we first simulated, extracted, and analyzed the scattering intensity of two types of rice of six temporal CP synthetic aperture radar (SAR) data under three transmitting modes. Then, during different phenology stages, the optimal parameters for distinguishing transplanting hybrid rice (T–H) and direct-sown japonica rice (D–J) were acquired. Finally, a decision tree classification model was established based on the optimal parameters to carry out the fine classification of the two types of rice and to verify the results. The results showed that this strategy can obtain a high classification accuracy for the two types of rice with an overall classification accuracy of more than 95% and a kappa coefficient of more than 0.94. In addition, and importantly, we found that the CP parameters in the 1103 period (harvest stage) were the best CP parameters to distinguish the two types of rice, followed by the 0730 (seedling–elongation stage), 0612 (seedling stage), and 0916 (heading–flowering stage) periods.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/rs14071644</doi><orcidid>https://orcid.org/0000-0002-0901-0577</orcidid><orcidid>https://orcid.org/0000-0002-5795-9533</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Classification compact polarimetric (CP) SAR Decision trees Elongation Feature recognition Flowering Global positioning systems GPS multi-mode and classification Object recognition Parameters Phenology Polarimetry Remote sensing Rice Scattering scattering intensity Seedlings Synthetic aperture radar Transmission |
title | Scattering Intensity Analysis and Classification of Two Types of Rice Based on Multi-Temporal and Multi-Mode Simulated Compact Polarimetric SAR Data |
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