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| Content Provider | Taylor & Francis Online |
|---|---|
| Author | Wang, Chongchang Xing, Zhurong Yang, Guijun Ma, Zhen |
| Abstract | The multi-source data fusion methods are rarely involved in VNIR and thermal infrared remote sensing at present. Therefore, the potential advantages of the two kinds of data have not yet been adequately tapped, which results in low calculation precision of parameters related with land surface temperature. A new fusion method is put forward where the characteristics of the high spatial resolution of VNIR (visible and near infrared) data and the high temporal resolution of thermal infrared data are fully explored in this paper. Non-linear fusion is implemented to obtain the land surface temperature in high spatial resolution and the high temporal resolution between the land surface parameters estimated from VNIR data and the thermal infrared data by means of GA-SOFM (genetic algorithms & self-organizing feature maps)-ANN (artificial neural network). Finally, the method is verified by ASTER satellite data. The result shows that the method is simple and convenient and can rapidly capture land surface temperature distribution of higher resolution with high precision. |
| Starting Page | 271 |
| Ending Page | 280 |
| Page Count | 10 |
| File Format | PDF HTM / HTML |
| ISSN | 10095020 19935153 |
| DOI | 10.1007/s11806-009-0093-4 |
| Journal | Geo-spatial Information Science |
| Volume Number | 12 |
| Issue Number | 4 |
| Language | English |
| Publisher | Taylor & Francis Group |
| Publisher Date | 2012-08-14 |
| Access Restriction | Open |
| Subject Keyword | VNIR data Thermal infrared Land surface parameter GA-SOFM mapping ANN P237 |
| Content Type | Text |
| Resource Type | Article |
| Subject | Geography, Planning and Development Computers in Earth Sciences |
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