Research On Spatio-temporal Data Query Method And Visualization Technology

Spatio-temporal data is a kind of high-dimensional data with complex structure and multi-level nesting.It has spatial and temporal characteristics.The complex spatio-temporal data emerges continuously.It is urgent for database researchers to propose effective query processing methods to meet the growing and complex and diverse query requirements of people.This article takes traffic data as the research object.The spatial data query method and visualization technology were studied.The main work of the thesis is as follows:1.spatio-temporal data often have missing,inconsistency and noise.In this paper,EMD is used to decompose the spatio-temporal data,and then the soft-threshold denoising is performed on the high-frequency components containing noise.and then the high-frequency component containing noise is denoised by wavelet transform soft threshold.Finally,experiments show that the denoising effect of the combination of EMD and wavelet transform is better than using one of the denoising methods.2.The space-filled curve Z curve is used to reduce the dimensionality of space-time data,and the conversion between high-dimensional low-dimensional data is accomplished by using the method of encoding and decoding.3.The Hcknn query method for parallel Skyline and historical moving object trajectories is studied.Use Maxdist_trajectory_rectangle distance metrics and pruning strategies are used to reduce memory space consumption and CPU cost.4.Research and analysis of the Geomesa distributed spatio-temporal database and Geomesa storage?query space-time data process,compared Geomesa and PostGISstorage and query space-time data efficiency,and use Geomesa visualization spatio-temporal data.