地理信息系统空间多维数据自动监测方法

为了解决传统监测方法有很大不确定性,监测结果不准确的问题,通过正交变换处理研究地理信息系统空间多维数据自动监测方法。对地理信息系统地形空间多维数据和道路空间多维数据进行可视化处理,利用人工神经网络对其进行降维映射。在保证数据项在低维空间中相对距离不变的情况下,通过正交变换处理,令空间数据在相邻时间的坐标偏移达到最小,帮助用户发现相邻时刻监测区域的不同之处,实现地理信息系统空间多维数据自动监测。结果表明:所提方法监测结果和人工统计结果最相符;所提方法监测F值一直高于0. 9。可见所提方法监测精度高,有很强的可行性与可靠性。

Automatic Monitoring method of Spatial Multidimensional data in Geographic Information system

In order to solve the problem that the traditional monitoring have great uncertainty and the monitoring results are not accurate, the automatic monitoring method of spatial multi-dimensional data in Geographic Information System is studied by orthogonal transformation processing method. In this paper, we visualize the terrain spatial multidimensional data and road spatial multidimensional data of Geographic Information System, and use artificial neural network to map them. Under the condition of keeping the relative distance of data items unchanged in low-dimensional space, the coordinate offset of spatial data in adjacent time is minimized by orthogonal transformation, which helps users to find the differences of monitoring areas at adjacent time, and realizes the automatic monitoring of spatial multi-dimensional data in Geographic Information System. The results show that the monitoring results of the proposed method are most consistent with those of manual statistics, and the F value of the proposed method is always higher than 0.9. It is obvious that the proposed method has high monitoring accuracy and strong feasibility and reliability.