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

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.

[1]  D. Lampkin,et al.  Evaluation of a novel inversion model for surface melt magnitude over the Greenland ice sheet during the 2002 ablation season , 2013 .

[2]  Xavier Fettweis,et al.  The 1988–2003 Greenland ice sheet melt extent using passive microwave satellite data and a regional climate model , 2006 .

[3]  Jennifer A. Francis,et al.  Has Arctic Sea Ice Loss Contributed to Increased Surface Melting of the Greenland Ice Sheet , 2016 .

[4]  M. Broeke,et al.  The modelled liquid water balance of the Greenland Ice Sheet , 2017 .

[5]  Marco Tedesco,et al.  Snowmelt detection over the Greenland ice sheet from SSM/I brightness temperature daily variations , 2007 .

[6]  Bo Jiang,et al.  Surface Shortwave Net Radiation Estimation from FengYun-3 MERSI Data , 2015, Remote. Sens..

[7]  Gabriele Moser,et al.  Partially Supervised classification of remote sensing images through SVM-based probability density estimation , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Rabul Hussain Laskar,et al.  Impulse noise removal using SVM classification based fuzzy filter from gray scale images , 2016, Signal Process..

[9]  Jungho Im,et al.  Support vector machines in remote sensing: A review , 2011 .

[10]  Kenneth C. Jezek,et al.  Classification of snow facies on the Greenland ice sheet using passive microwave and SAR imagery , 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).

[11]  Xavier Fettweis,et al.  The role of albedo and accumulation in the 2010 melting record in Greenland , 2011 .

[12]  Huadong Guo,et al.  Automated ice-sheet snowmelt detection using microwave radiometer measurements , 2013 .

[13]  Jon Atli Benediktsson,et al.  Fusion of Support Vector Machines for Classification of Multisensor Data , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Konrad Steffen,et al.  Passive microwave‐derived snow melt regions on the Greenland Ice Sheet , 1995 .

[15]  Fuzhong Weng,et al.  Introduction to the Special Issue on the Chinese FengYun-3 Satellite Instrument Calibration and Applications , 2012, IEEE Trans. Geosci. Remote. Sens..

[16]  Crystal B. Schaaf,et al.  Evaluation of Satellite Remote Sensing Albedo Retrievals over the Ablation Area of the Southwestern Greenland Ice Sheet , 2017 .

[17]  Xavier Fettweis,et al.  The 1979–2005 Greenland ice sheet melt extent from passive microwave data using an improved version of the melt retrieval XPGR algorithm , 2007 .

[18]  Qingshan Liu,et al.  Improving the Spatial Resolution of FY-3 Microwave Radiation Imager via Fusion With FY-3/MERSI , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[19]  Konrad Steffen,et al.  Comparison of brightness temperatures from SSMI instruments on the DMSP F8 and FII satellites for Antarctica and the Greenland ice sheet , 1995 .

[20]  Marcos E. Orchard,et al.  On-line estimation of the aerobic phase length for partial nitrification processes in SBR based on features extraction and SVM classification , 2018 .

[21]  David G. Long,et al.  Comparison of methods for melt detection over Greenland using active and passive microwave measurements , 2006 .

[22]  Konrad Steffen,et al.  Snowmelt on the Greenland Ice Sheet as Derived from Passive Microwave Satellite Data , 1997 .

[23]  Matthew F. McCabe,et al.  Detecting ice-sheet melt area over western Greenland using MODIS and AMSR-E data for the summer periods of 2002–2006 , 2011 .

[24]  Lorenzo Bruzzone,et al.  Classification of hyperspectral remote-sensing data with primal SVM for small-sized training dataset problem☆ , 2008 .