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Cluster Computing

, Volume 22, Supplement 4, pp 8301–8308 | Cite as

Near-surface snowmelt detection on the Greenland ice sheet from FengYun-3 MWRI data

  • Xingdong WangEmail author
  • Zhankai Wu
  • Xinwu Li
Article
  • 79 Downloads

Abstract

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.

Keywords

FengYun-3 satellite Snowmelt detection Greenland ice sheet XPGR algorithm SVM algorithm 

Notes

Acknowledgements

This research was supported by the National Key Research and Development Program of China (Grant No. 2016YFA0600302), and supported by Natural Science Foundation of China (No. 41606209), and supported by the Fujian Provincial Key Laboratory of Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, China (JYG1707), and supported by the Fundamental Research Funds for the Henan Provincial Colleges and Universities (2015QNJH16). We thank the Chief Editor of the Journal and the anonymous reviewers for their time and effort, which will significantly improves the manuscript.

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Information Science and EngineeringHenan University of TechnologyZhengzhouChina
  2. 2.Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingChina
  3. 3.Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics TechnologyFujian Normal UniversityFuzhouChina

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