Extending geographic information systems to urban morphological analysis with a space syntax approach

Branches of complexity theory have been widely employed in geographic information systems (GIS) to explore phenomena that appear in urban environments. Among these, space syntax, as an urban morphological application of complexity theory, has attracted increasing attention in recent years. Accordingly, many computer-based tools have been developed to realize related analysis spatially, especially those that can be integrated as functions with GIS. In this thesis, a space syntax tool – Axwoman – is redeveloped and tested as an extension of ESRI ArcGIS Desktop in order to fulfill certain specific needs in urban morphological analysis. It is primarily used to calculate all space syntax measures for several urban systems and to explore the relationships between these measures. To meet the needs for this new version of Axwoman, several functions have been updated and changed, for drawing, coloring, and classifying axial lines as maps for visual thinking; ticking overpasses and excluding them from computing space syntax parameters; and integrating AxialGen and Axwoman. In accordance with this, several case studies have been performed on the urban street networks in large cities. In this paper, Stockholm was chosen as the study object at both the urban level and the building level. After the scaling analysis and time efficiency analysis, the results are also interpreted from a structural point of view and in terms of how the function of space is subject to its morphological structure. Finally, the connectivity of axial lines (a spatial measurement in space syntax theory) was found to follow a power-law distribution. Through this work, the new edition of Axwoman generating satisfactory outputs, the research have proved that the connectivity of axial lines follows a lognormal distribution or a power-law-like distribution, which is one of the heavy-tailed distributions. In addition, it was have found that axial lines better for capture the underlying urban morphologies showed in their study on redefining the generated axial lines from street center lines. Moreover, fewer longest axial lines will show up on the maps, just as coincidental as the shape of mental maps, which proved that the axial line representations can be a powerful tool for urban studies