書誌事項
- タイトル別名
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- Fuzzy Linear Regression Analysis of Land-cover Classification Using Remotely Sensed Data
- リモートセンシングデータ オ モチイタ ファジィ センケイ カイキ ブンセキ
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抄録
In this study developed is a new method for land-cover classification of remotely sensed data. The proposed method bases its modeling structure on so-called category decomposition principle, estimating categorical proportions of a mixel rather than assigning only one category to it. Classification algorithm is established in the framework of fuzzy linear regression analysis so that observed radiance data of the subject mixel may be contained, at least to a predetermined degree, in the estimated fuzzy set of radiance which is accomplished by the weighted sum of category specific spectra expressed by fuzzy numbers. Validity tests using Landsat TM data show that the proposed method substantially outperforms three existing methods compared, the quadratic programming method based on category decomposition idea, the linear discriminant analysis method and the maximum likelihood method, by up to 40% in terms of root mean square error of estimation and also the proposed method has a kind of robustness in that it can make relatively accurate estimates compared to the existing methods even though inexact categorical characteristics of spectra are input to the model.
収録刊行物
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- 電気学会論文誌C(電子・情報・システム部門誌)
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電気学会論文誌C(電子・情報・システム部門誌) 118 (11), 1562-1569, 1998
一般社団法人 電気学会
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詳細情報 詳細情報について
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- CRID
- 1390001204607030272
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- NII論文ID
- 130006842995
- 10002815355
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- NII書誌ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL書誌ID
- 4588417
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- NDL
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