Visual Analysis of High-Dimensional Spatiotemporal Data

Visual analysis method is one of the important methods of high dimensional spatiotemporal data mining, which provides more possibilities for the sustainable development of cities. This paper takes the visualization of high-dimensional spatiotemporal data of air quality as the research data basis, because air quality is related to everyone's health and the sustainable development of the city. Economic prosperity promotes the development of the city, but also brings the deterioration of air quality. This paper introduces visual analysis technology based on map and parallel coordinate visual analysis technology to visually analyze and explore the high-dimensional spatiotemporal data set of air quality, so as to reveal the potential new knowledge and correlation in the data, improve the mutual influence mechanism of air quality and economic development and the relationship between them. Through the interactive visualization of the high-dimensional economic and air quality spatiotemporal data set of 31 provinces in China, the development trend and spatiotemporal distribution characteristics of air quality and economic factors in China are obtained. This has also led to some useful findings that can serve as a scientific basis for policy making and industrial restructuring.