Data analytics for modeling soil moisture patterns across united states ecoclimatic domains

Data analytics for modeling soil moisture patterns across united states ecoclimatic domains
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DOI:
10.1109/bigdata.2017.8258536
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发表时间:
2017-12
期刊:
2017 IEEE International Conference on Big Data (Big Data)
影响因子:
--
通讯作者:
T. Kitson;Paula Olaya;Elizabeth Racca;Michael R. Wyatt;M. Guevara;R. Vargas;M. Taufer
T. Kitson;Paula Olaya;Elizabeth Racca;Michael R. Wyatt;M. Guevara;R. Vargas;M. Taufer
中科院分区:
其他
文献类型:
--
作者:
T. Kitson;Paula Olaya;Elizabeth Racca;Michael R. Wyatt;M. Guevara;R. Vargas;M. Taufer

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我们的海报展示了一个数据分析策略,使科学家能够在美国各地以不同的分辨率模拟土壤湿度数据的模式。我们建立在格瓦拉和合作者以前的工作有三个贡献。首先,我们引入了国家生态观测站网络提出的土壤湿度对气候区的划分。其次,利用主成分分析方法减少了土壤湿度建模中使用的拓扑参数。第三,我们提出了一种高效的土壤湿度数据建模和可视化工作流程。
Our poster presents a data analytics strategy to enable scientists to model patterns of soil moisture data at different resolutions across the United States. We build upon previous work of Guevara and co-authors with three contributions. First, we introduce divisions of soil moisture into the climatic regions proposed by the National Ecology Observatory Network. Second, we reduce the topological parameters used in modeling soil moisture using Principal Component Analysis. Third, we present an efficient workflow for modeling and visualizing soil moisture data.