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LandQ~(v1): A GIS cluster-based management information system for arable land quality big data

机译:Landq〜(v1):基于GIS集群的管理信息系统,适用于耕地质量大数据

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In the era of spatial big data, geographic information system (GIS) faces many opportunities and challenges. The first challenge for future GIS is how to store and manage the spatial big data efficiently. For example, in 2013, the volume of Chinese arable land quality (ALQ) dataset is up to 2.51TB with ESRI Shapefile format, and traditional GIS development pattern with standalone version is not meeting the needs including storage, query, analysis and visualization. To solve above problems, in this paper, we present a system framework, LandQ~(v1), based on the GIS cluster to support arable land quality big data management and analysis in geospatial domain. Firstly, it describes the design of the system architecture with three layers in details, and implemented by different technologies accordingly. Secondly, three models, data storage model, service release model, and data calling model, are developed to solve the key problems of each layer in the system framework. And then, LandQ~(v1) is developed with the WPF, GIS cluster, Oracle database and C# language. Finally, through application and system test, the results show that LandQ~(v1) with GIS map tools, data query and other functions can be meted the needs in high performance, which will lay the foundation for arable land big data analyzing in the future.
机译:在空间大数据时代的到来,地理信息系统(GIS)面临许多机遇和挑战。对于未来GIS的第一个挑战是如何存储和有效管理的空间大数据。例如,在2013年,中国耕地质量(ALQ)数据集的体积达到与ESRI shape文件格式2.51TB,与单机版的传统GIS的发展模式不能满足需求,包括存储,查询,分析和可视化。为了解决上述问题,在本文中,我们提出了一个系统的框架,LandQ〜(V1),基于GIS集群支持耕地质量大数据管理和分析地理空间领域上。首先,它描述了系统体系结构与细节三层的设计,并通过不同的技术相应的执行。其次,三种型号,数据存储模型,服务模型发布和数据调用模型,开发,解决了系统架构中每个层的关键问题。然后,LandQ〜(V1)与WPF,GIS集群,Oracle数据库和C#语言开发。最后,通过应用程序和系统测试,结果表明,LandQ〜(V1)与GIS地图工具,数据查询等功能,可以判刑高性能的需求,这将在未来奠定了耕地的大数据分析的基础。

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