Analyzing Antarctic ice sheet snowmelt with dynamic Big Earth Data
Big Earth Data—big data associated with Earth sciences—can potentially revolutionize research on climate change, sustainable development, and other issues of global concern. For example, analyzing massive amounts of satellite imagery of polar environments, which are sensitive to the effects of clima...
| Published in: | International Journal of Digital Earth |
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| Main Authors: | , , , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Taylor & Francis Group
2021
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| Subjects: | |
| Online Access: | https://doi.org/10.1080/17538947.2020.1798522 https://doaj.org/article/5508958527b741049b6a931badbe2591 |
| Summary: | Big Earth Data—big data associated with Earth sciences—can potentially revolutionize research on climate change, sustainable development, and other issues of global concern. For example, analyzing massive amounts of satellite imagery of polar environments, which are sensitive to the effects of climate change, provides insights into global climate trends. This study proposes a method to use Big Earth Data to explore changes in snowmelt over the Antarctic ice sheet from 1979 to 2016. The method uses Zernike moments to observe melt area in Antarctica and uses the Mann-Kendall test to detect temporal changes and abnormal information about the continent's melt area. The melting trend in the time-series data matched the changes in temperature and seasonal transitions. The results do not demonstrate significant change in the area of surface melt; however, abrupt changes in melt conditions linked to temperature changes over the Antarctic ice sheet were observed within the time series. The experiment results demonstrate that the proposed method is robust, adaptive, and capable of extracting the core features of melting snow. |
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