支持时空耦合计算的HTM-ST日地空间系统数据组织模型
HTM-ST: A Data Model Supporting Spatio-Temporal Coupled Computation for Solar-Terrestrial System
查看参考文献18篇
文摘
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数据组织模型是对科学数据进行有效管理、共享与应用的基础。日地空间物理学科通常采用基于语义标注的传统数据组织模型,但是该模型忽略了数据间的时空关系,难以支持大规模数据处理与关联分析,应建立一种支持时空计算的数据组织模型,从而有效支持当前日地空间物理领域对数据快速发现、精细结构识别、耦合关系研究与时空演化分析等方面的应用需求。鉴于此,本文提出了HTM-ST离散化时空数据组织模型,该模型在层次三角网格的基础上,在时间维度通过等长剖分进行扩展,从而形成离散化的时空剖分,采用时-空耦合编码将高维的剖分单元组织到一维空间中,并基于上述剖分结构与编码算法在HBase环境下设计了模型的存储方案。本文利用多颗极轨卫星的能量粒子探测数据实现了该数据组织模型的原型示范系统,并设计了基于该模型的时空查询算法和地方时全球数据插值算法,用于对该模型进行实验验证。实验分析表明,HTM-ST模型具有高效性和鲁棒性,可以作为面向时空关系的日地空间物理数据组织与存储基础。 |
其他语种文摘
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Data Model is the basis for the effective management, sharing and application of scientific data. Nowadays, the sematic data model is a conventional and dominant data organization method in the solar-terrestrial physics domain which aims to describe data along with its various metadata, such as observatories, instruments, and data types etc. However, it's difficult to support mass data processing and correlation analysis because the model neglects the temporal and spatial relations among data. Hence, a data model supporting spatio-temporal computation should be established to facilitate data discovery, fine structure identification, coupling relation research and spatio-temporal evolution analysis and other research hotspots of solar-terrestrial physics. Therefore, this paper proposed a computable spatio-temporal data model, HTM-ST that supports these applications. On the basis of the HTM global discrete grid, this model established discrete spatio-temporal subdivision by extending HTM's spherical units to equal-divided time dimension. Besides, a novel spatio-temporal coupled coding algorithm is described to represent these high-dimensional units in the one-dimensional space. Meanwhile, the model's storage scheme is designed and implemented in the HBase platform based on the model's subdivision structure and coding algorithm. In this paper, a prototype system is implemented to evaluate the efficiency of the model, by comparing multiple spatio-temporal queries over energetic particle data observed by five polar orbit satellites. The experimental results show that HTM-ST data model is more efficient and robust. It could be used as the solar-terrestrial physics data organization and storage foundation for spatio-temporal relationship. |
来源
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地球信息科学学报
,2017,19(6):735-743 【核心库】
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DOI
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10.3724/SP.J.1047.2017.00735
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关键词
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数据组织模型
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层次三角网格
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时空编码
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日地空间
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地址
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中国科学院国家空间科学中心数据网络技术实验室, 北京, 100190
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语种
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中文 |
文献类型
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研究性论文 |
ISSN
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1560-8999 |
学科
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地球物理学 |
基金
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中国科学院科研信息化专项
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文献收藏号
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CSCD:6012569
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参考文献 共
18
共1页
|
1.
King T. SPASE 2.0: A standard data model for space physics.
Earth Science Informatics,2010,3(1/2):67-73
|
被引
3
次
|
|
|
|
2.
张康聪.
地理信息系统导论,2014
|
被引
2
次
|
|
|
|
3.
赵学胜.
全球离散格网的空间数字建模,2007
|
被引
20
次
|
|
|
|
4.
Mahdavi-Amiri A. A survey of digital earth.
Computers & Graphics,2015,53:95-117
|
被引
4
次
|
|
|
|
5.
Sahr K. Geodesic discrete global grid systems.
Cartography and Geographic Information Science,2003,30(2):121-134
|
被引
94
次
|
|
|
|
6.
Nault L. Nga introduces global area reference system.
Pathfinder: The Geospatial Intelligence Magazine,2006,11:19-20
|
被引
1
次
|
|
|
|
7.
程承旗.
空间信息剖分组织导论,2012
|
被引
40
次
|
|
|
|
8.
Geoffrey H.
Dutton. Lecture notes in earth sciences: A hierarchical coordinate system for geoprocessing and cartography,1999
|
被引
1
次
|
|
|
|
9.
Szalay A S.
Indexing the sphere with the hierarchical triangular mesh,2007
|
被引
1
次
|
|
|
|
10.
Kunszt P Z. The hierarchical triangular mesh.
Mining the sky,2001:631-637
|
被引
1
次
|
|
|
|
11.
Vince A. Arithmetic and Fourier transform for the PYXIS multi-resolution digital Earth model.
International Journal of Digital Earth,2009,2(1):59-79
|
被引
18
次
|
|
|
|
12.
Lukatela H. Ellipsoidal area computations of large terrestrial objects.
The First International Conference on Discrete Grids,2000
|
被引
1
次
|
|
|
|
13.
Kolar J. Representation of the geographic terrain surface using global indexing.
Proceeding of 12th International Conference on Geoinformatics,2004:321-328
|
被引
6
次
|
|
|
|
14.
Hoel E. Big Data: Using ArcGIS with apache hadoop.
Esri International Developer Summit,2014
|
被引
1
次
|
|
|
|
15.
Eldawy A. Spatialhadoop: A mapreduce framework for spatial data.
Data Engineering (ICDE), 2015 IEEE 31st International Conference on,2015:1352-1363
|
被引
1
次
|
|
|
|
16.
Nishimura S. MD-HBase: Design and implementation of an elastic data infrastructure for cloud-scale location services.
Distributed and Parallel Databases,2013,31(2):289-319
|
被引
14
次
|
|
|
|
17.
Aji A. Hadoop GIS: A high performance spatial data warehousing system over mapreduce.
Proceedings of the VLDB Endowment,2013,6(11):1009-1020
|
被引
20
次
|
|
|
|
18.
George L.
HBase: The definitive guide: Random access to your planet-size data,2011
|
被引
5
次
|
|
|
|
|