首页> 外文会议>ISPRS Technical Commission VIII Mid-Term Symposium >IDENTIFICATION OF PROMINENT SPATIO-TEMPORAL SIGNALS IN GRACE DERIVED TERRESTRIAL WATER STORAGE FOR INDIA
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IDENTIFICATION OF PROMINENT SPATIO-TEMPORAL SIGNALS IN GRACE DERIVED TERRESTRIAL WATER STORAGE FOR INDIA

机译:识别印度恩典奠定突出的时空信号

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Fresh water is a necessity of the human civilization. But with the increasing global population, the quantity and quality of available fresh water is getting compromised. To mitigate this subliminal problem, it is essential to enhance our level of understanding about the dynamics of global and regional fresh water resources which include surface and ground water reserves. With development in remote sensing technology, traditional and much localized in-situ observations are augmented with satellite data to get a holistic picture of the terrestrial water resources. For this reason, Gravity Recovery And Climate Experiment (GRACE) satellite mission was jointly implemented by NASA and German Aerospace Research Agency - DLR to map the variation of gravitational potential, which after removing atmospheric and oceanic effects is majorly caused by changes in Terrestrial Water Storage (TWS). India also faces the challenge of rejuvenating the fast deteriorating and exhausting water resources due to the rapid urbanization. In the present study we try to identify physically meaningful major spatial and temporal patterns or signals of changes in TWS for India. TWS data set over India for a period of 90 months, from June 2003 to December 2010 is use to isolate spatial and temporal signals using Principal Component Analysis (PCA), an extensively used method in meteorological studies. To achieve better disintegration of the data into more physically meaningful components we use a blind signal separation technique, Independent Component Analysis (ICA).
机译:淡水是人类文明的必要性。但随着全球人口的增加,可用淡水的数量和质量受到损害。为了缓解这种潜意识问题,必须提高关于全球和区域淡水资源动态的理解水平,包括地表和地下水储量。随着遥感技术的发展,传统和大量本地化的原位观察与卫星数据增强,以获得地面水资源的整体画面。出于这个原因,通过美国宇航局和德国航空航天研究机构联合实施的重力恢复和气候实验(Grace)卫星使命 - DLR来映射重力潜力的变化,除去大气和海洋效果,主要是由地面储存的变化引起的(TWS)。由于快速城市化,印度也面临着恢复快速恶化和疲惫的水资源的挑战。在本研究中,我们试图识别印度的物理上有意义的主要空间和时间模式或变化的信号。从2003年6月到2010年6月到2010年6月的INDED为90个月的TWS数据用于隔离使用主成分分析(PCA)的空间和时间信号,是一种广泛的气象研究方法。为了更好地解体数据进入更物理上有意义的组件,我们使用盲信号分离技术,独立分量分析(ICA)。

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