| タイトル | Pattern recognition of clouds and ice in polar regions |
| 著者（英） | Welch, R. M.; Kuo, K. S.; Sengupta, S. K.; Sundar, C. A.; Carsey, F. D. |
| 著者所属（英） | South Dakota School of Mines and Technology|Jet Propulsion Lab., California Inst. of Tech. |
| 発行日 | 1990-01-01 |
| 言語 | eng |
| 内容記述 | The study is based on AVHRR imagery and results from Landsat high-spatial-resolution scenes. Among the textual features investigated are the gray level difference vector (GLDV), and sum and difference histogram (SADH) approaches as well as gray level run length, spatial-coherence, and spectral-histogram measures. The traditional stepwise discriminant analysis and neural-network analysis are used for the identification of 20 Arctic surface and cloud classes. A principal-component analysis and hybrid architecture employing a modularized competitive learning layer are utilized. It is pointed out that the cloud-classification accuracy comparable to that of back-propagation could be achieved with a training time two orders of magnitude faster. |
| NASA分類 | METEOROLOGY AND CLIMATOLOGY |
| レポートNO | 91A36614 |
| 権利 | Copyright |
| URI | https://repository.exst.jaxa.jp/dspace/handle/a-is/348331 |
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