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As the nature of geographic environment is a complex
system, researches in this field are anticipated. In
particular, the urban street networks as complex
networks are brought forth in this study with help of
the Geographic Information System (GIS). This book
explored the topological patterns of a sample of 40
US urban street networks, from both analytical and
visual perspectives. The scale free properties for
the connectivity degree and length of the urban
streets networks were examined. Moreover, the new
methods based on Maximum Likelihood Estimation
together with goodness-of-fit test were performed, in
order to brought solid and accurate results.
Simultaneously, thanks to the large network
visualization tool (LaNet-vi), which is based on
k-core decomposition algorithm, the topological
networks of the urban streets were able to be
presented visually. With help of the platform from
GIS, the spatial information can be successfully
retrieved to offer more meaningful visualization
effects.
system, researches in this field are anticipated. In
particular, the urban street networks as complex
networks are brought forth in this study with help of
the Geographic Information System (GIS). This book
explored the topological patterns of a sample of 40
US urban street networks, from both analytical and
visual perspectives. The scale free properties for
the connectivity degree and length of the urban
streets networks were examined. Moreover, the new
methods based on Maximum Likelihood Estimation
together with goodness-of-fit test were performed, in
order to brought solid and accurate results.
Simultaneously, thanks to the large network
visualization tool (LaNet-vi), which is based on
k-core decomposition algorithm, the topological
networks of the urban streets were able to be
presented visually. With help of the platform from
GIS, the spatial information can be successfully
retrieved to offer more meaningful visualization
effects.