基于线性参照系统的高铁沉降数据集成模型  

High-speed Railway Subsidence Data Management Integration Model Based on Linear Referencing System

作　　者：张倩宁 黄泽纯[1,2] 洪安东[1,2] 尚海滨[3] 

机构地区：[1]西南交通大学地球科学与环境工程学院,四川成都610031 [2]西南交通大学高速铁路运营安全空间信息技术国家地方联合工程实验室,四川成都610031 [3]成都理工大学旅游与城乡规划学院,四川成都610059

出　　处：《地理空间信息》2016年第1期99-101,6,共3页Geospatial Information

基　　金：中央高校基本科研业务费专项资金资助项目(2682014CX017);长江学者和创新团队发展计划资助项目(IRT13092)

摘　　要：针对高铁沉降监测数据的海量特性,以及传统管理方式存在的效率不高、可视化效果不好的问题,设计了一种基于线性参照系统有效管理和显示高铁沉降监测数据的集成模型。该模型中,高铁路网以路径要素集存储,高铁沿线非空间数据以事件表的形式存储,由此实现高铁沉降监测相关的空间数据和属性数据的线性建模与集成。同时,使用Arc Engine组件与.NET平台实现了沉降监测数据空间查询和可视化表达功能,可形象地反映高铁线路与沉降监测点的分布状况,更易于进行沉降数据的可视化分析、预测和评估。数据集成模型实现了非空间数据和空间数据的一体化管理,有效地减少了数据存储冗余,提高了高铁变形监测数据管理的效率,对我国高速铁路的建设与运营安全的海量监测数据管理具有一定的参考价值。Because of the mass data of the high-speed railway subsidence monitoring, the poor efficiency and bad visualization of the traditional management ways, this paper proposed a new model which was to apply linear referencing system to manage and display the subsidence monitoring data of high-speed railway. In the model, high-speed railway network data was stored in route feature classes, non-spatial data in event tables. Based on ArcE ngine and.NET platform, the model realized the spatial query and visualization representation functions, gave expression to the distribution of high-speed railway and subsidence monitoring points, and contributed to subsidence data analysis, trend prediction and evaluation. The model also realized the integration of non-spatial data and spatial data, effectively reduced the data redundancy, improved the subsidence monitoring data manage efficiency of high-speed railway. This study would be the certain reference for the mass monitoring data management of high-speed railway construction and operation safety.

关 键 词：线性参照系统 沉降监测 数据集成 空间数据库 可视化 

分 类 号：P258[天文地球—测绘科学与技术]