The number of cases of forms, which could be created with the backgrounds of human beings with different identities, the variety of environments, various combinations of design principles, and the fusion of these, would be too many to calculate. The p... The number of cases of forms, which could be created with the backgrounds of human beings with different identities, the variety of environments, various combinations of design principles, and the fusion of these, would be too many to calculate. The possibility that beauty exists that is commonly preferred by the general public can be based on the fact that many works of art exist that most of us consider as masterpieces. There may be the principle of integration that controls the principle of design, which may be the origin of preferred beauty that makes human beings feel beautiful. This principle of integration is more likely to be concretely found in the circumstances received through perception rather than by essential introspection. The principle of integration mentioned above is the keyword of this study, "VC (Visual Complexity)". The visual complexity was first mentioned in the psychology of art by Rudolf Arnheim(1966), who studied, based on Gestalt psychology, what makes human beings see works of art. Therefore, it can be said that the academic foundation of visual complexity is Gestalt psychology. The visual complexity is also closely connected with order. The higher the order, the lower the visual complexity, whereas the lower the order, the higher the visual complexity. Ultimately, the proper state of order in which each maintains balance is the optimum state of visual complexity, in which state works of art are created that are preferred by human beings. The majority of research studies on visual complexity are mostly those conducted on the flat surface such as polygon, pattern and texture, and so there are few studies conducted in three-dimensional urban space. Therefore, the purposes of this study are as follows: First, to present the standards for establishing the factors that affect the VC (visual complexity) in urban space and establish factors in VC. Second, to present the methods for analyzing established VC factors and present new methods for studying VC. Third, to present the relationship between the fundamental characteristics of order in artificial landscape and the VC factors presented by this study. Fourth, to analyze the sectional photographs of the streets, i.e., the subject of analysis, using presented VC factors and analyze the relationship between the degrees of VC judged by the general public and its influence. Fifth, to make a model for VC and secure the objectivity of the VC factors presented by the researcher by analyzing the correlation. Chapter 3 explains four standards for establishing VC factors with a new research method and establishes the ten VC factors(eleven VC factors) which are expected to influence the degrees of VC(high-medium-low) appropriate for these standards. The Eleven VC factors are composed of visual physical quantity, quality of vision, visual composition. Visual physical quantity are composed of ①the number of vertical/the number of horizontal(facade), ②the number of vertical/the number of horizontal(perspective1). ③the number of vertical/the number of horizontal(perspective2). Quality of vision are composed of ④pattern of street floor, ⑤ornament of architecture. Visual composition are composed of ⑥variation of street floor, ⑦visual sequence, ⑧overlap(short range view and medium range view), ⑨section(street), ⑩D/H, ⑪extent of sign/extent of genuine skin of architecture(facade). Also, it presents the summary of the established factors and the ways of analysis and establishes the hypothesis and the framework for analysis (finally, six VC factors (①, ②, ③, ⑤, ⑦, ⑪) are analyzed in this study). In Chapter 4, in order to secure the data for statistical analysis, we analyzed a total of 42 photographs taken from all of the above streets as the framework for analysis (six VC factors) of this study and did data coding together with the results of the general public survey. Chapter 4 covers the relationship analysis for VC factors and the degrees, and includes six steps of analysis process. Analysis 1 used the one-to-one correlation of all the variables (six VC factors and three degrees of VC covered in Chapter 3). Analysis 2 used the correlation analysis to see how the VC factors individually influence the degrees of VC. Based on the results of the correlation, Analysis 3 investigated the differences in distance using ANOVA. Analysis 4 used the multiple regression analysis to see which VC factors are relevant to the degrees of VC when integrated individual VC factors act in combination. Analysis 5 used the weighted regression analysis to see which combination of VC factors are relevant to an individual VC with no distinction in the degrees of VC. Using only the three significant VC factors obtained from Analysis 5 as variables. Analysis 6 used the weighted regression analysis again and drew a significant VC model and the weighted regression analysis.
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