A Comprehensive Data Preparation for Insights on Mobility Patterns in Sofia
Abstract
This study investigates mobility patterns in Sofia, Bulgaria, focusing on commute travelers. The research utilizes data from a mobile network operator, providing unique insights into the spatial and temporal movements of residents. The data set presents peculiarities such as the impact of Covid-19 restrictions and vacation periods on travel frequency. The research involves a detailed data preparation process, including extracting and analyzing geospatial data using Google Places API, identifying and cleaning duplicate geographic data points, visualizing geographical data and performing point-in-polygon operations with Python libraries, and integrating travelers' data. This comprehensive approach ensures precise, reliable, and insightful results, potentially informing future city planning and transportation policies.
References
2. Hall, Thornberg, et. al., (2015-2022) “How much distance does 0.001∘in latitude or longitude represent?” Earth Science Stack Exchange. https://earthscience.stackexchange.com/questions/6843/how-much-distance-does-0-001-circ-in-latitude-or-longitude-represent
3. Hägerstraand, T. (1970). What about people in regional science? Papers in Regional Science, 24(1), 7-24.
4. Zandbergen, P. A. (2009). Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning. Transactions in GIS, 13, 5-25.
5. McKinney, W. (2010). Data Structures for Statistical Computing in Python. Proceedings of the 9th Python in Science Conference, 51-56.
6. Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2015). Geographic Information Science and Systems. John Wiley & Sons.
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