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タイトル
  • ja XバンドおよびCバンドSARデータを併用した機械学習アルゴリズムによる圃場の作物分類
  • en Crop Classification by Machine Learning Algorithm with Combination of X- and C-band SAR Data
作成者
    • ja 山谷, 祐貴 en YAMAYA, Yuki
    • ja 小林, 伸行 en KOBAYASHI, Nobuyuki
    • ja 望月, 貫一郎 en MOCHIZUKI, Kan-ichiro
    • ja 野田, 萌 en NODA, Megumi
アクセス権 open access
権利情報
  • ja © 2018 一般社団法人 日本写真測量学会
  • en © 2018 Japan Society of Photogrammetry and Remote Sensing
主題
  • NDC 614
内容注記
  • Abstract en A crop classification method using satellite data is proposed as an alternative to the existing ground survey. In this study, crop types were classified using two kinds of SAR data (i.e., TerraSAR-X X-band dual-polarization data and Radarsat-2 C-band fully-polarization data) and Random Forests. Sigma naught polarimetric parameters were calculated from SAR data and classifications were conducted using the following four different datasets ; Case 1 : all parameters calculated from Radarsat-2, Case 2 : all parameters calculated from Radarsat-2 and sigma naught calculated from TerraSAR-X data, Case 3 : all parameters calculated from Radarsat-2 and polarimetric parameters calculated from TerraSAR-X data, and Case 4 : all parameters calculated from Radarsat-2 and both sigma naught and polarimetric parameters calculated from TerraSAR-X. The highest overall accuracy of 0.934 was achieved by Case 4, and there were significant differences with the other classification results (p>0.05, based on Z-test). These results reveal that combining two kinds of SAR data can be improved classification accuracy.
日付
    Issued2018-05-11
言語
  • jpn
資源タイプ journal article
出版タイプ VoR
資源識別子 HDL http://hdl.handle.net/2115/73921
関連
  • isIdenticalTo DOI https://doi.org/10.4287/jsprs.57.78
収録誌情報
  • ja 写真測量とリモートセンシング en Journal of the Japan society of photogrammetry and remote sensing
  • 巻57 号2 開始ページ78 終了ページ83
ファイル
    • fulltext 57_78.pdf
    • 473.28 KB (application/pdf)
      • Issued2018-05-11
コンテンツ更新日時 2023-07-26