Antarctic Snowmelt Detection Using QuikSCAT Data Based on Wavelet Transform Combined With A Generalized Gaussian Model
Surface snowmelt on Antarctic ice sheets is not only an important indicator of global climate change but also a key controllingfactor of the global climate. The QuikSCAT microwave scatterometer is highly sensitive to the liquid water content of snow, and it can beused macroscopically, rapidly, objec...
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ftdpipublojs:oai:ojs.dpi-journals.com:article/3860 2023-05-15T14:01:14+02:00 Antarctic Snowmelt Detection Using QuikSCAT Data Based on Wavelet Transform Combined With A Generalized Gaussian Model Wang, Xingdong Wang, Cheng 2017-01-23 application/pdf http://www.dpi-journals.com/index.php/JRST/article/view/3860 eng eng Journal of Residuals Science & Technology http://www.dpi-journals.com/index.php/JRST/article/view/3860/2950 Copyright (c) 2017 Journal of Residuals Science & Technology Journal of Residuals Science & Technology; Vol 13, No 8 2376-578X 1544-8053 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article 2017 ftdpipublojs 2018-01-16T08:16:48Z Surface snowmelt on Antarctic ice sheets is not only an important indicator of global climate change but also a key controllingfactor of the global climate. The QuikSCAT microwave scatterometer is highly sensitive to the liquid water content of snow, and it can beused macroscopically, rapidly, objectively, and effectively to monitor and assess Antarctic snowmelt condition. Based on a long time seriesof QuikSCAT data, a new automatic threshold segmentation method was proposed in this study for the detection of Antarctic snowmeltonset date, end date, and duration. The method takes multi-scale edge information extracted from backscattering coefficients by wavelettransform, and a generalized Gaussian model automatically fits the optimal wet and dry snow classification threshold. The method, whichdoes not rely on measured data, inherits and develops the advantage of snowmelt detection and it achieves the goal of an effective Antarcticsnowmelt monitoring system. Comparison of the snowmelt results with temperatures at eight automatic weather stations demonstrated thefeasibility of using scatterometer data with the proposed algorithm for Antarctic snowmelt detection. Article in Journal/Newspaper Antarc* Antarctic DPI Journals (Destech Publications) Antarctic |
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Open Polar |
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DPI Journals (Destech Publications) |
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ftdpipublojs |
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English |
description |
Surface snowmelt on Antarctic ice sheets is not only an important indicator of global climate change but also a key controllingfactor of the global climate. The QuikSCAT microwave scatterometer is highly sensitive to the liquid water content of snow, and it can beused macroscopically, rapidly, objectively, and effectively to monitor and assess Antarctic snowmelt condition. Based on a long time seriesof QuikSCAT data, a new automatic threshold segmentation method was proposed in this study for the detection of Antarctic snowmeltonset date, end date, and duration. The method takes multi-scale edge information extracted from backscattering coefficients by wavelettransform, and a generalized Gaussian model automatically fits the optimal wet and dry snow classification threshold. The method, whichdoes not rely on measured data, inherits and develops the advantage of snowmelt detection and it achieves the goal of an effective Antarcticsnowmelt monitoring system. Comparison of the snowmelt results with temperatures at eight automatic weather stations demonstrated thefeasibility of using scatterometer data with the proposed algorithm for Antarctic snowmelt detection. |
format |
Article in Journal/Newspaper |
author |
Wang, Xingdong Wang, Cheng |
spellingShingle |
Wang, Xingdong Wang, Cheng Antarctic Snowmelt Detection Using QuikSCAT Data Based on Wavelet Transform Combined With A Generalized Gaussian Model |
author_facet |
Wang, Xingdong Wang, Cheng |
author_sort |
Wang, Xingdong |
title |
Antarctic Snowmelt Detection Using QuikSCAT Data Based on Wavelet Transform Combined With A Generalized Gaussian Model |
title_short |
Antarctic Snowmelt Detection Using QuikSCAT Data Based on Wavelet Transform Combined With A Generalized Gaussian Model |
title_full |
Antarctic Snowmelt Detection Using QuikSCAT Data Based on Wavelet Transform Combined With A Generalized Gaussian Model |
title_fullStr |
Antarctic Snowmelt Detection Using QuikSCAT Data Based on Wavelet Transform Combined With A Generalized Gaussian Model |
title_full_unstemmed |
Antarctic Snowmelt Detection Using QuikSCAT Data Based on Wavelet Transform Combined With A Generalized Gaussian Model |
title_sort |
antarctic snowmelt detection using quikscat data based on wavelet transform combined with a generalized gaussian model |
publisher |
Journal of Residuals Science & Technology |
publishDate |
2017 |
url |
http://www.dpi-journals.com/index.php/JRST/article/view/3860 |
geographic |
Antarctic |
geographic_facet |
Antarctic |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_source |
Journal of Residuals Science & Technology; Vol 13, No 8 2376-578X 1544-8053 |
op_relation |
http://www.dpi-journals.com/index.php/JRST/article/view/3860/2950 |
op_rights |
Copyright (c) 2017 Journal of Residuals Science & Technology |
_version_ |
1766270839872815104 |