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Study for Multi-Resources Spatial Data Fusion Methods in Big Data Environment

机译:大数据环境下多资源空间数据融合方法研究

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摘要

The rapid development and extensive application of geographic information system (GIS) and the advent of the age of big data bring about the generation of multi-resources spatial data, which makes data integration and fusion share more difficult due to the differences on data source, data accuracy and data modal. Meanwhile, study for multi-resources spatial data fusion methods has an important practical significance for reducing the production cost of geographic data, accelerating the updating speed of existing geographical information and improving the quality of GIS big data. To expound the formation and developing trends of multi-resources spatial data fusion methods systematically, and on the basis of referring to lots of related technical documents both at home and abroad, this paper makes a conclusion and discussion about multi-resources spatial data fusion methods, and foresees the prospects of data fusion in big data environment, which has certain reference value for the related research work.
机译:地理信息系统(GIS)的快速发展和广泛应用以及大数据时代的来临,导致了多资源空间数据的产生,由于数据源的差异,使得数据集成和融合共享变得更加困难,数据准确性和数据模态。同时,多资源空间数据融合方法的研究对于降低地理数据的生产成本,加快现有地理信息的更新速度,提高GIS大数据质量具有重要的现实意义。为系统地阐述多资源空间数据融合方法的形成和发展趋势,在参考国内外许多相关技术文献的基础上,对多资源空间数据融合方法进行了总结和讨论。并预见了大数据环境下数据融合的前景,对相关研究工作具有一定的参考价值。

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