高分解能衛星画像を用いたディシジョンツリー法に基づく樹種分類法の開発

• 河邑 眞

  豊橋技術科学大学

• 辻野 和彦

  福井工業高等専門学校

• 辻子 祐二

  福井工業高等専門学校

書誌事項

タイトル別名

• Development of a Forest Species Classification Method Based on a Decision Tree Method Using High Resolution Satellite Imagery
• コウ ブンカイノウ エイセイ ガゾウ オ モチイタ ディシジョンツリーホウ ニ モトヅク ジュシュ ブンルイホウ ノ カイハツ

抄録

A forest species classification method based on a decision tree method which used high resolution satellite imagery is proposed in this study. The proposed method consists of two parts. In the first part the extraction of forest areas is accomplished by the maximum likelihood method. In the second part 10 kinds of forest species are classified in the extracted forest areas using the decision tree method and IKONOS pan-sharpen multi-spectral data. In the decision tree method the parameters to divide two branches are obtained from the spectral analysis or the texture analysis of the IKONOS data for each forest species.<BR>The study was carried out for a mountain area located in the Yamato and Minami district, Gifu Prefecture, in Japan. The results of forest species discrimination were evaluated by using independent field survey data. It is concluded that the comprehensive extraction accuracy in all forest species is about 67% and the proposed method is applicable to the forest monitoring and the planning as a useful tool.

収録刊行物

• 写真測量とリモートセンシング

  写真測量とリモートセンシング 44 (2), 54-67, 2005

  一般社団法人 日本写真測量学会

詳細情報

• CRID: 1390282679054303744
• NII論文ID: 10030896578
• NII書誌ID: AN00111450
• DOI: 10.4287/jsprs.44.2_54
• ISSN: 18839061
• ISSN: 02855844
• ISSN: http://id.crossref.org/issn/02855844
• NDL書誌ID: 7361799
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I7361799
• 本文言語コード: ja
• データソース種別:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可