Microwave radiometer SSM/I data and scatterometer QuikSCAT data have been widely used for the icesheet near-surface snowmelt detection based on their sensitivity to liquid water present in snow. In order to improve th...Microwave radiometer SSM/I data and scatterometer QuikSCAT data have been widely used for the icesheet near-surface snowmelt detection based on their sensitivity to liquid water present in snow. In order to improve the Antarctic ice-sheet near-surface snowmelt detection accuracy, a new Antarctic icesheet near-surface snowmelt synergistic detection method was proposed based on the principle of complementary advantages of SSM/I data(high reliability) and QuikSCAT data(high sensitivity) by the use of edge detection model to automatically extract the edge information to get the distribution of Antarctic snowmelt onset date, snowmelt duration and snowmelt end date. The verification result shows that the proposed snowmelt synergistic detection method improves the detection accuracy from about 75% to 86% based on AWS(Automatic Weather Stations) Butler Island and Larsen Ice Shelf. The algorithm can also be applied to other regions, which provides methodological support and supplement for the global snowmelt detection.展开更多
基金supported by National Natural Science Foundation of China(Grant No. 41606209)supported by National Key Research and Development Program of China (Grant No. 2016YFB0501501)+3 种基金supported by Fujian Provincial Key Laboratory of Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, China(Grant No. JYG1707)supported by Polar Science Strategic Research Foundation of China (Grant No. 20150312)supported by the Fundamental Research Funds for the Henan Provincial Colleges and Universities (Grant No. 2015QNJH16)supported by Science and technology project of Zhengzhou Science and Technology Bureau(Grant No. 20150251)
文摘Microwave radiometer SSM/I data and scatterometer QuikSCAT data have been widely used for the icesheet near-surface snowmelt detection based on their sensitivity to liquid water present in snow. In order to improve the Antarctic ice-sheet near-surface snowmelt detection accuracy, a new Antarctic icesheet near-surface snowmelt synergistic detection method was proposed based on the principle of complementary advantages of SSM/I data(high reliability) and QuikSCAT data(high sensitivity) by the use of edge detection model to automatically extract the edge information to get the distribution of Antarctic snowmelt onset date, snowmelt duration and snowmelt end date. The verification result shows that the proposed snowmelt synergistic detection method improves the detection accuracy from about 75% to 86% based on AWS(Automatic Weather Stations) Butler Island and Larsen Ice Shelf. The algorithm can also be applied to other regions, which provides methodological support and supplement for the global snowmelt detection.
