A Multiple Networks Model of Space Syntax

• Main Authors: Yu-YouChiang, 蔣於佑
• Other Authors: Han-Liang Lin
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/14952438792564753933

碩士 === 國立成功大學 === 都市計劃學系碩博士班 === 100 === 　　Space syntax is a set of techniques for interpreting the spatial configuration by topologically indexing the free space based on graph theory. Space syntax argues that the configuration of spatial networks influences the movement of human beings. Thus, space syntax studies the moving behavior of human beings via the quantification and analyses of spatial configuration. People mainly rely on the visual interpretation to learn the street space. Therefore, space syntax models its primary tool, “Axial Map”, based on the “visibility” of pedestrians to represent the connectivity of urban systems in “longest and fewest” axial lines and decompose the organization of street network via the topological configuration of axial maps. 　　However, the walking range of people is mainly around the scale of community, local or district. Most of the prior studies applied space syntax on local-scale analyses of street network as well. Nonetheless, the movement from homes to jobs, homes to CBDs, or homes to leisure, etc., is usually across city or region. Such movement relies on the transferring among buses and railways, combining the networks of street, bus and railway routes, which the networks formed by buses and railways provide the connection for people to move across local street networks. Pedestrians can go farther through the transit mode combined by “routes-stations”. Therefore, the analyses of spatial connectivity of cities or regions should not only contain the street network but also other spatially connecting systems. 　　This article aims at a space syntax solution for multiple networks, combining street network and railway network including rapid transit systems. To achieve the goal, the definition of the axial map and spatial analysis indices should be adjusted to describe different networks of street and railways. Secondly, we have to find out the modeling solution. The existing software such as UCL Depthmap 10 and Mindwalk 1.0 are not designed for the analyses of multiple networks. The article develops the solution through ESRI ArcGIS to improve a complete model including the procedure of establishing and analyzing, in space syntax for applying it on the analyses of large-scale street networks. 　　The data of Kaohsiung City were used in experimental study to examine the practicability of the model. We compared the results of multiple networks including TRA and KMRT systems with street network, and found that the spatial structure is actually different because of the public transit networks. Thus, the suggestion for further researches is the application of the multiple networks model on the patterns or trends of different urban elements. The practicability of the model can then be examined, and the relationships between the urban configurations of varied transit models and other elements of urban form can also be understood.