Today various spaces are existing, and people each have different impressions of them. This causes ambiguity of decision and evaluation when designing spaces. For the problem, several techniques to analyze spaces quantitatively have been studied. But the relationships among them were not obvious. The purpose of this study was to define relationships among techniques for space visibility analysis. We reviewed exiting studies that analyze space visibility quantitatively, and derived 12 indicators from them. Originally, the method of this study have to apply to numerous and several spaces for obtain general conclusion. But we had not enough resources for the works. As an alternative, we set 9 space cases to apply indicators and the cases were adjusted from one space. First we calculated indicators with space cases. And we analyzed characteristics of indicators and similarity among indicators. Finally we derived results as follows : 1) Circularity have peculiar tendencies. That sharply fluctuated with space cases. 2) Similarity among some indicators is very strong and we suggested to use only one of them because of an overlap. 3) Skewness have no any similarity with other indicators. 4) Visual access and visual exposure are distinguished by similarities with variation. 5) Using clustering and multi dimension scaling, we schematized relationships among indicators and classified indicators.
영어초록
Today various spaces are existing, and people each have different impressions of them. This causes ambiguity of decision and evaluation when designing spaces. For the problem, several techniques to analyze spaces quantitatively have been studied. But the relationships among them were not obvious. The purpose of this study was to define relationships among techniques for space visibility analysis. We reviewed exiting studies that analyze space visibility quantitatively, and derived 12 indicators from them. Originally, the method of this study have to apply to numerous and several spaces for obtain general conclusion. But we had not enough resources for the works. As an alternative, we set 9 space cases to apply indicators and the cases were adjusted from one space. First we calculated indicators with space cases. And we analyzed characteristics of indicators and similarity among indicators. Finally we derived results as follows : 1) Circularity have peculiar tendencies. That sharply fluctuated with space cases. 2) Similarity among some indicators is very strong and we suggested to use only one of them because of an overlap. 3) Skewness have no any similarity with other indicators. 4) Visual access and visual exposure are distinguished by similarities with variation. 5) Using clustering and multi dimension scaling, we schematized relationships among indicators and classified indicators.
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