Welcome to the GitHub repository for my thesis project titled "Decoding City Network: Exploring Urban Structure and Spatial Event Interplay Through Multiple Centrality Assessment". This repository is dedicated to housing the research, data, analyses, and findings of my extensive study on urban network structures and their correlation with spatial events, using multiple centrality assessments.
Contains datasets used in the analysis, including urban street network data, spatial event records (like road accidents), and other relevant urban data. Each dataset is accompanied by a metadata file describing its source, structure, and any preprocessing steps taken.
This folder houses all the coding scripts used for data processing, network analysis, centrality computations, and statistical analysis. The scripts are primarily in Python, utilizing libraries like NetworkX, Pandas, and GeoPandas for network analysis and data handling.
Jupyter notebooks detailing the step-by-step analytical process, from data cleaning to advanced network analysis. These notebooks include comments and visualizations to make the research process transparent and reproducible.
Includes the output of analyses such as centrality measures, correlation matrices, and spatial event analyses. Also contains visual representations of networks, spatial data, and any inferential statistical tests conducted.
Detailed documentation on how to use the scripts, interpret the results, and a guide to the structure of the repository. It also includes a summary of the research methodology and a link to the full thesis document.
The full text of the thesis, including an introduction to the study, literature review, methodology, results, discussion, and conclusions.
The primary goal of this repository is to provide a comprehensive resource for academics, urban planners, and data scientists interested in urban network analysis. By sharing the data, code, and findings, this project aims to foster collaboration, encourage further research, and contribute to the development of smarter, more resilient urban environments.
For any additional information or inquiries, please contact me