ABSTRACT

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.

摘要

大地球数据（与地球科学相关的大数据）可能会彻底改变有关气候变化，可持续发展以及全球关注的其他问题的研究。例如，分析对气候变化影响敏感的极地环境的大量卫星图像，可以洞悉全球气候趋势。这项研究提出了一种利用大地球数据来探索1979年至2016年南极冰盖上融雪变化的方法。该方法使用Zernike矩来观测南极洲的融雪面积，并使用Mann-Kendall检验来检测时间变化和异常信息。关于大陆的融化区。时间序列数据中的融化趋势与温度和季节变化的变化相匹配。结果没有证明表面熔体的面积有显着变化。然而，在时间序列内观察到与南极冰盖上温度变化有关的融化条件突然变化。实验结果表明，该方法是鲁棒的，自适应的，能够提取融雪的核心特征。