| Summary: | Recently, there has been an increasing interest in looking at urban environment as a complex system. More and more researchers are paying attention to the study of the configuration of urban space as well as human social activities within it. It has been found that correlation exists between the morphological properties of urban street network and observed human social movement patterns. This correlation implies that the influence of urban configurations on human social movements is no longer only revealed from the sense of metric distance, but also revealed from topological and geometrical perspectives. Metric distances, topological relationships and angular changes between streets should be considered when applying space syntax analysis to an urban street network. This thesis is mainly focused on the comparison among metric, topological and angular analyses based on three kinds of urban street representation models: natural streets, axial lines and axial segments. Four study areas (London, Paris, Manhattan and San Francisco) were picked up for empirical study. In the study, space syntax measures were calculated for different combinations of analytical methods and street models. These theoretical space syntax accessibility measures (connectivity, integration and choice) were correlated to the corresponding practical human movement to evaluate the correlations. Then the correlation results were compared in terms of analytical methods and street representation models respectively. In the end, the comparison of results show that (1) natural-street based model is the optimal street model for carrying out space syntax analysis followed by axial lines and axial segments; (2) angular analysis and topological analysis are more advanced than metric analysis; and (3) connectivity, integration and local integration (two-step) are more suitable for predicting human movements in space syntax. Furthermore, it can be hypothesized that topological analysis method with natural-street based model is the best combination for the prediction of human movements in space syntax, for the integration of topological and geometrical thinking.
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