• CDR
• noise removal
• mobile phone data
• dynamic population estimation
• Call Detail Records

The prevalent use of mobile phones by individuals generate an immense amount of information about the mobility of people for network operators. This data which is called Call Detail Records can be used to study the movement behaviors of individuals, the collective behavior of the population in different circumstances such as big events, and evacuation. Policy-makers can utilize this data for planning purposes. One of the main problems with mobile phone data is their sparsity and low position accuracy. In this thesis, we analyzed different sources of mobile phone positioning errors and removed the noises for subsequent analysis purposes. We then obtained the stay locations from the trajectories of users and used them as an indicator of the population in different spatial areas and temporal intervals. We also used this data to generate mobility networks for each user. We augmented our research with a visualization dashboard that is suitable to analyze the mobile phone data, allowing us to apply different filters on different dimensions.