論文

査読有り
2012年

Generation of Pseudo-fully Polarimetric Data from Dual Polarimetric Data for Land Cover Classification

PROCEEDINGS OF INTERNATIONAL CONFERENCE ON COMPUTER VISION IN REMOTE SENSING
  • Bhogendra Mishra
  • ,
  • Junichi Susaki

開始ページ
262
終了ページ
267
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1109/CVRS.2012.6421272
出版者・発行元
IEEE

A linear relationship among the HH, HV, and VV components of polarimetric synthetic aperture radar (SAR) data is studied. A regression model was developed to predict the real and imaginary parts of the VV polarimetric component from the HH and HV components in dual polarimetric SAR and the resulting dataset is called pseudo-fully polarimetric SAR data. Freeman-Wishart classification was applied to evaluate the preservation of scattering characteristics in the pseudo-fully polarimetric dataset. A kappa coefficient is 0.81 indicates very good agreement between the two classification results. An SVM was used for the land cover classification. Finally, post-processing was implemented to remove noise in the form of isolated pixels. A VNIR-2 optical data taken over the same area at nearly same time was used as ground truth data to assess the classification accuracy. The land cover classification result obtained from the SVM shows that using the pseudo-fully polarimetric data gives more than a 2% improvement of mean producer's accuracy over dual polarimetric datasets.

リンク情報
DOI
https://doi.org/10.1109/CVRS.2012.6421272
J-GLOBAL
https://jglobal.jst.go.jp/detail?JGLOBAL_ID=201502833017848438
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000318878700050&DestApp=WOS_CPL
ID情報
  • DOI : 10.1109/CVRS.2012.6421272
  • J-Global ID : 201502833017848438
  • Web of Science ID : WOS:000318878700050

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