Computational Methods for Extracting Mobility Patterns from Raw GPS Data

This master's thesis focuses on the analysis of GPS data, specifically on Floating Car Data (FCD) and smartphone positioning. The study is divided into two main sections. The first section analyzes road conditions, traffic patterns, and congestion levels using FCD from vehicles. The research aims to provide insights into traffic flow and identify congestion areas. Additionally, a model is proposed to predict pollution levels based on the FCD, offering a novel approach to environmental monitoring and urban planning. In the second section, utilizing smartphone positioning data, the thesis examines the movement patterns, stay locations, and origins of passengers in relation to a specific airport. It investigates where local residents depart from, whether they use competing airports, their destinations, the origins of incoming passengers, and their stay locations. This analysis provides valuable information on airport usage, passenger behavior, and urban mobility, which can be used to enhance airport infrastructure and improve tourism management.