3D Visualization Of City Data And User Behavior Analysis Based On VR

With the development of smart city construction and the maturity of Virtual Reality technology,users have higher requirements for data visualization technology.At the same time,more scholars attach more attention to the study of user-centered 3D data visualization.The development of Virtual Reality technology provides a novel platform for multi-heterogeneous city data visualization.In order to improve the intuitiveness and accuracy of the comprehensive analysis of city data in the construction of smart cities,it is necessary to build an immersive city data visualization framework based on Virtual Reality.Visual variables,the basis of visualization,consist of various kind of forms.At present,most visualization platforms use single visual variable for visualization,which ignores the uniqueness of human visual perception.Therefore,this article summarizes data visualization framework process,proposing a multiple visual variable mapping model and user behavior analysis model in the Virtual Reality environment from the perspective user’s visual cognition.The user task cognitive experiments are designed to verify the effectiveness of proposed mode.Besides,this paper makes a detailed analysis of user behavior data and tries to explore the user’s visual preferences and behavior characteristics in the VR environment.The main research contents and innovations of this paper are as follows:(1)Combined with the general process of visualization and the characteristics of visual variables,this paper selects seven visual variables for preliminary threedimensional visualization expression,and analyzes their applicability in Virtual Reality space.This research realizes the framework of city data visualization based on VR environment according to the intuitiveness of users’ visual perception,integrating Virtual Reality equipment into Unity3 D engine.In this paper,the main visual variable combined with other auxiliary visual variables is used to map the city attribute data,and a VR-based mapping model of multiple visual variables is proposed.(2)Based on the cognitive theory of geographic information visualization,the correlation between visualization,user interaction behavior and user visual cognition is analyzed.This paper forms the task-driven relationship model of "task-stimulusresponse-analysis".In the analysis of user behavior,the traditional statistical analysis method is used to summarize the rules of visual design.Considering the sequential characteristics of user behavior,this research proposes a user behavior analysis model based on Virtual Reality using deep learning method.(3)This paper confirms user cognition experiments in a Virtual Reality environment for the purpose of verifying effectiveness of the proposed model.The experiment is divided into two task modes: single visual variable and multiple visual variables.Through statistical analysis and questionnaire survey,the effectiveness of the task-based visual representation of multiple visual variables is verified,and it is also found that the visual coding using HSV color space is more efficient than the traditional color map visualization.The deep learning method is used to effectively classify two user visual patterns.This paper wants to utilize the visual coding suggestions as the further optimization of visualization scheme from the summary of the user’s visual preference and user behavior characteristics.(4)Finally,this paper develops the grain depot display platform based on Web and the grain depot training system based on VR,which applies the VR technology and visual development technology to the grain depot field.The summarized visual variable coding rules are used to the actual operation the data visualization of the grain depot to improve the intuitive feeling of the users.