Spatial And Temporal Big Data Analysis And Visualization Of Floating Vehicles Under Cloud Architecture

The current development of mobile Internet,Internet of things,cloud computing and other technologies has generated massive data beyond any previous era.Spatio-temporal big data is the fusion of spatio-temporal data and big data,which has the dual value of big data and geographical space-time.Mining and discovering spatio-temporal big data is one of the hot spots in GIS academia at present.Compared with traditional data,spatio-temporal big data has the characteristics of large volume,fast update and multi-dimension,etc.,and it has higher technical requirements in the process of processing spatio-temporal big data.In this paper,by taking advantage of the cloud and big data framework to about 120 g for 7 months in Wuhan city taxi trajectory data analysis and processing,and use the mature of the front frame and visualization of the processing results are visual,mining the travel law of urban residents in Wuhan city,taxi operation situation and situation of Wuhan municipal traffic in Wuhan city,Wuhan area between liquidity and influence the results of the analysis,etc.In order to guide residents travel activities,taxi operation strategy,municipal traffic management and Wuhan city planning.The specific research and work contents of this paper are as follows:(1)Analyzing the quality problems of the original data set,and propose solutions to improve the data quality according to the quality problems of the original data set.By building the Hadoop big data processing platform on the elastic cloud server,a complete set of data processing process is designed to perform data cleaning,OD point extraction,geographic coordinate transformation and other computing and processing work on the taxi track data.Effectively improve the efficiency of data processing,and reduce the cost of processing.(2)The spatial and temporal patterns of residents' travel characteristics and taxi operations were studied from different dimensions.By statistical analysis of OD point datasets in combination with meteorological data,the average daily change of taxi order quantity and order efficiency under different meteorological conditions was obtained.By statistical analysis of OD point datasets under special dates,different dates were obtained.The average daily change of taxi order quantity and order efficiency;through the statistical analysis of daily order efficiency and no-load time,the results of time and space analysis of taxi operation in Wuhan were obtained.(3)The traffic congestion situation in Wuhan and the regional attractiveness and mobility were analyzed.By stratifying and coloring the speed threshold,the traffic congestion of Wuhan in different time periods can be obtained.Through the visualization of OD points at different time periods by thermal map,the hot spots of residents going out at different time periods and getting off at different time periods in Wuhan are obtained.Since the attractive coefficient,this paper puts forward area regional indexes such as flow coefficient,the regional flow equilibrium coefficient of Wuhan city is mainly administrative range,business circle,the transportation hub of attraction and liquidity is analyzed,and generate the OD matrix to the quantitative analysis of the results,further through the OD matrix generated heat Descartes tries to quantify the results more intuitive,finally through the map from the geographical spatial flow condition between the population in different regions.(4)Using the Bootstrap front-end framework and Echarts visualization library builds the visualization system,the heat map,map,congestion figure,regional liquidity statistics,order statistics menu is divided into five level,visualization of spatial analysis results reasonable layout,realized the visualization of trajectory data analysis results of time and space,improve the visual analysis results.