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| Content Provider | Springer Nature Link |
|---|---|
| Author | Zhang, Chengwei Yu, Fan Wang, Chenxi Yang, Jianyu |
| Copyright Year | 2011 |
| Abstract | We describe how the Unit-Feature Spatial Classification Method (UFSCM) can be used operationally to classify cloud types in satellite imagery efficiently and conveniently. By using a combination of Interactive Data Language (IDL) and Visual C++ (VC) code in combination to extend the technique in three dimensions (3-D), this paper provides an efficient method to implement interactive computer visualization of the 3-D discrimination matrix modification, so as to deal with the bi-spectral limitations of traditional two dimensional (2-D) UFSCM. The case study of cloud-type classification based on FY-2C satellite data (0600 UTC 18 and 0000 UTC 10 September 2007) is conducted by comparison with ground station data, and indicates that 3-D UFSCM makes more use of the pattern recognition information in multi-spectral imagery, resulting in more reasonable results and an improvement over the 2-D method. |
| Starting Page | 601 |
| Ending Page | 611 |
| Page Count | 11 |
| File Format | |
| ISSN | 02561530 |
| Journal | Advances in Atmospheric Sciences |
| Volume Number | 28 |
| Issue Number | 3 |
| e-ISSN | 18619533 |
| Language | English |
| Publisher | SP Science Press |
| Publisher Date | 2011-05-05 |
| Publisher Place | Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | cloud-type classification unit-feature spatial classification method three dimensions Geophysics/Geodesy Meteorology/Climatology |
| Content Type | Text |
| Resource Type | Article |
| Subject | Atmospheric Science |
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