Semantic Visual Variables And Augmented Pan-spatial Geovisualization

Pan-spatial(referring to the “human-cyber-physical” ternary space)information is a collection of various information describing complex spatio-temporal phenomena in the ternary space.It is the main content of spatio-temporal big data and the foundation of space intelligent computing and platform construction.“A picture is worth a thousand words”,visualization is one of the main means to transform information into human understandable form,especially when the clues hidden in the data are highlighted and expressed in the fused form of symbol and immersion,when combined with human vision and domain knowledge can turn a large amount of heterogeneous data into valuable knowledge.This is one of the problems that need to be broken through in the construction of smart city platforms,and it is also an important requirement for people to improve spatial thinking.However,Pan-spatial information has the characteristics of multi-source,heterogeneous,multi-dimensional and complex correlation,which makes its visualization face the difficult problem of perceptible presentation for different users(viz."not perceptible,not clear,not understandable").To this end,this dissertation summarizes the existing research on visual variables and geovisualization theory,aims at the adaptive visualization and analysis needs of multi-modal spatio-temporal data,and deeply studies how to optimize the structure of multi-modal spatio-temporal data to build information-enriched scenes that conform to human perception,and to construct the augmented Pan-spatial geovisualization methods which can present high-dimensional spatiotemporal data in easily understandable forms.And also,it fully takes into account the constraints of multi-level semantic visual variables in line with the laws of human cognition,and is aiming to break through the bottleneck of visual overload and visual chaos in the process of symbolization and immersion of visualization,and finally resulting in adaptive visualization that is just the right combination of forms with “continuous and discrete,dynamic and static,detailed and generalized,realistic and abstract”.The specific research content is as follows:(1)The connotation of augmented Pan-spatial geovisualization.The ternary spaces of human-cyber-physical are tightly coupled.The Pan-spatial(referring to the human-cyberphysical ternary space)information is a collection of various information describing complex spatiotemporal phenomena in the ternary space,including various tangible or intangible entities and their states,attributes,behaviors,and relationships,etc.How to mutually enhance the expression and easily perceptible presentation of the Pan-spatial information,the Panspatial information must be effectively integrated,and a multi-granular spatio-temporal object scene model with a unified description is constructed;the classification and description of the augmented Pan-spatial geovisualization tasks are defined;On this basis,an augmented Panspatial geovisualization method and a symbolic model description based on the visual variable system are constructed.(2)Multi-level semantic visual variable system.Visual variables are used to transform information into forms that the human visual system can perceive.Its development has gone from traditional "map variables" to "GIS variables" to "pan-map visualization variables",from "two-dimensional,static variables" to "three-dimensional,dynamic variables" and then to "multi-form mixed compound variables".The existing research on visual variables focuses on the method of "information-graphic mapping",that is,the perceptual level,but lacks the "intelligence" derived from the balance of "importance" and "insignificance",that is,the semantical understanding of information and visualization tasks,it is difficult to satisfy the augmented expression of the fused human,cyber and physical space,the Pan-spatial multigranularity spatio-temporal object scene.Based on the existing research on visual variables,this dissertation analyzes their characteristics and constructs a highly generalized and scalable multi-level semantic visual variable system,which enhances the ability of visual variables to express information,and meets the needs of diversified expression of complex information scene.(3)Task-driven multi-level focus visualization mechanism.Focus+Context(F+C)is an important method to solve information overload in visualization.The existing F+C visualization method research mainly focuses on specific data structures or view forms,and lacks the understanding and abstraction of the deep-seated reasons for focusing,while the augmented Pan-spatial geovisualization is aimed at multi-source and heterogeneous information,and the visualization tasks,forms,views and users are extensive,diverse and complex,making the existing F+C visualization methods difficult to meet such needs.To this end,this dissertation analyzes the essence of focus in depth,and attribute focus to the effects of three core factors: Degree of interest(Do I),Level of details(Lo D)and Degree of abstraction(Degree of abstraction,Do A),which control the degree of focus from tasks,data,and perception separately.They control the degree of "easy perception" of scene objects/entities/data as they get changed,when apply with appropriate visual expressions and thus balacing the visual information load,improving the visual guidance and enhancing the efficiency of visual information transmission.Finally,we introduce an eye tracking based evaluation method,which break through the problem that traditional geographic visualization is dominated by subjective factors,and it is difficult to objectively quantify and adjust the visualization parameters.(4)Prototype system and experimental analysis.For augmented Pan-spatial decisionmaking support of smart city,a prototype system of multi-terminal-multi-view collaborative augmented Pan-spatial geovisualization was designed and developed,and finally tested by an experiment taking emergency command of high-rise building fire as an example.Eye movement tests proved the effectiveness of the proposed semantic visual variables and focus visualization mechanism in multi-level visualization tasks: “city scale global disaster situation awareness”,“on-site command in districts scale” and “fire fighting and rescue in disaster areas”.The attracting efficiency and attention of the subjects to areas of interest have been significantly improved.