Extraction of Area Liquefied by Earthquake Using Self-Organizing Map.
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- HOSOKAWA Masafumi
- Earthquake Disaster Section, National Research Institute of Fire and Disaster
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- ITO Yosuke
- Department of Civil Engineering, Takamatsu National College of Technology
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- HOSHI Takashi
- Department of Computer and Information Sciences, Faculty of Engineering, Ibaraki University
Bibliographic Information
- Other Title
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- 自己組織化マップ(SOM)による液状化領域の抽出
- ジコ ソシキカ マップ SOM ニ ヨル エキジョウカ リョウイキ ノ チュウシュツ
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Abstract
A supervised classification method using a self-organizing map (SOM) is proposed to classify remote sensing data. SOM has a characteristic that a probability density function of input data is represented as a feature map. The proposed method is realized by creating a category map from the feature map of SOM. The category map can visualize characteristics of SPOT HRV data and it is also employed as a supervised classification method. The proposed method extracts liquefied area in Kobe (Japan) damaged by the 1995 Hyogoken Nanbu earthquake using the SPOT HRV data and the category map. As an experimental result, it is shown that classification accuracies of the proposed method are higher than those of the maximum likelihood and the back-propagation methods.
Journal
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- Journal of the Japan society of photogrammetry and remote sensing
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Journal of the Japan society of photogrammetry and remote sensing 38 (6), 14-23, 1999
Japan Society of Photogrammetry and Remote Sensing
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Details 詳細情報について
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- CRID
- 1390282679053908608
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- NII Article ID
- 10004968804
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- NII Book ID
- AN00111450
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- ISSN
- 18839061
- 02855844
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- NDL BIB ID
- 4957899
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed