Discovering Transit-Oriented Development Region Using Urban Data

The rapid expansion of urban space and population results in a series of urban problems, such as traffic congestion, environmental degradation, and energy shortage. Transit-Oriented Development (TOD) has become a reliable solution to urban sustainable development, which can reshape the urban form and improve its quality. However, current research on TOD bias in policy formulation and statistical analysis.This thesis focuses on leveraging urban data to answer three critical questions in TOD research:what region looks like under TOD concept, which regions have the potential to be TOD regions, and how to construct these TOD regions to meet the need of mixed function. At first, for region partition, this thesis proposes a connected component based clustering algorithm, which merges the large amount of public transport stations into representative cluster stations as region centers, and then Voronoi algorithm is applied to locate the region boundaries according to the cluster centers. For TOD region identification, this thesis presents link importance based random walk. Considering the importance of various transportations, it is easy for the method to randomly walk to nodes with higher link importance, and further to recognize the most valuable regions to be TODs. For discovering functions of TOD regions, this thesis introduces the approach of multi-factor based function characterization which combines both the static linguistic factor and human mobility factor. The approach defines a cost function, which is the difference between what the region is actually functioning and what the region reflects in both static level and dynamic level. Afterwards, it derives the actual function distribution of regions with gradient descent.At last, this thesis utilizes three datasets from Hangzhou, including public transportation lines and stops, points of interest, and taxi traces to validate the proposed methods. The experiment results show that the proposed methods are of superiority to solve the problems of region partition, TOD region identification, and function characterization. In the meantime, the results provide support for Hangzhou to construct a TOD city.