Near-surface snowmelt detection on the Greenland ice sheet from FengYun-3 MWRI data
Autor: | Zhan-Kai Wu, Xinwu Li, Xing-Dong Wang |
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Rok vydání: | 2018 |
Předmět: |
Computer Networks and Communications
Computer science Scanning multichannel microwave radiometer Energy balance Greenland ice sheet 020206 networking & telecommunications 02 engineering and technology Radiation Polarization (waves) Snow Snowmelt 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Software Microwave Remote sensing |
Zdroj: | Cluster Computing. 22:8301-8308 |
ISSN: | 1573-7543 1386-7857 |
DOI: | 10.1007/s10586-018-1743-9 |
Popis: | The melt extent on the Greenland ice sheet plays an important role in energy balance, and the Arctic and global climates. The micro-wave radiation imager (MWRI) is one of the major payloads of Chinese second-generation polar-orbiting meteorological satellite, FengYun-3 (FY-3), and it is similar to the special sensor microwave/image (SSM/I). The cross-polarized gradient ratio (XPGR) is mainly applied in the scanning multichannel microwave radiometer (SMMR) (18 GHz horizontal polarization (18 H) and 37 GHz vertical polarization (37 V)), the advanced microwave scanning radiometer-earth observing system (AMSR-E) (18.7 GHz horizontal polarization (18 H) and 36.5 GHz vertical polarization (36 V)) and SSM/I (19.3 GHz horizontal polarization (19 H) and 37 GHz vertical polarization (37 V)), which increases the differences between dry and wet snow. The hyperplane of support vector machine (SVM) is used to detect the melt information based on the XPGR data on the Greenland ice sheet, which has higher detection accuracy comparing with the existing threshold methods in theory. The results were compared with the SSM/I data (threshold = − 0.0154), and the results show that the proposed method (That is XPGR combining with SVM) for MWRI data is feasible for the detection of the near-surface snowmelt information on the Greenland ice sheet. |
Databáze: | OpenAIRE |
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