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Utilization of four-component scattering power decomposition method for glaciated terrain classification
http://hdl.handle.net/10191/30086
http://hdl.handle.net/10191/30086a535966c-96fc-430e-9818-bfe126223edc
名前 / ファイル | ライセンス | アクション |
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2014-10-09 | |||||
タイトル | ||||||
タイトル | Utilization of four-component scattering power decomposition method for glaciated terrain classification | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Utilization of four-component scattering power decomposition method for glaciated terrain classification | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | decomposition | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | PALSAR | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Himalayan | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | glaciated terrain | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
著者 |
Singh, Gulab
× Singh, Gulab× 山口, 芳雄× Park, Sang-Eun |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Glaciated terrain classification is important for hydrological and climate change modelling. For this purpose, fully polarimetric Advanced Land Observation Satellite-Phase Array L-band Synthetic Aperture Radar (ALOS-PALSAR) data has been used over Indian Himalayan glaciated region. PALSAR data has been analyzed based on the three and four component scattering decomposition methods for glaciated terrain classification. These methods have been applied on multi-looked 3 × 3 coherency matrix of ALOS-PALSAR data. The analysis of these methods shows that the Freeman and Durden three-component scattering power decomposition (3-CSPD) method has over estimation problem in volume backscattering component as compared to the Yamaguchi four-component scattering power decomposition (4-CSPD) method. After finding suitability of 4-CSPD method over Himalayan glaciated terrain, it has been combined with complex Wishart distribution for supervised classification of ALOS-PALSAR image. By this way, an overall accuracy has been found to be 93.38%. Even this procedure shows very high accuracy but discrimination between vegetation and glacier snow/ice classes was not properly done. To overcome this ambiguity, the probability difference between surface backscattering and volume backscattering has been introduced as further steps in classification procedure. | |||||
書誌情報 |
Geocarto International en : Geocarto International 巻 26, 号 5, p. 377-389, 発行日 2011 |
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出版者 | ||||||
出版者 | Taylor & Francis | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 10106049 | |||||
書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA10729367 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | info:doi/10.1080/10106049.2011.584978 | |||||
権利 | ||||||
権利情報 | © 2011 Taylor & Francis | |||||
権利 | ||||||
権利情報 | This is an Accepted Manuscript of an article published by Taylor & Francis Group in Geocarto International on 09/06/2011, available online: http://www.tandfonline.com/10.1080/10106049.2011.584978. | |||||
著者版フラグ | ||||||
値 | author |