This dissertation proposes an exploratory analytical tool for examining spatio-temporal pat-terns in any area of interest for urban and traffic planning. By combining solely Open-Source technologies to create a user-friendly analytical tool, planners can easily adjust the tool to fit multiple purposes, such as keeping track of the improvements towards reaching UN's Sustainable Development Goals or finding congested areas in urban areas. The latter has been done throughout this study, using a large set of Origin-Destination pairs, collected from cars in Denmark during 2019.
For the case study, the morning and afternoon traffic internally in Copenhagen and Frederiksberg municipalities are compared, to examine whether the flow of cars is different in the morning than in the afternoon, as well as to examine if there are any areas that are more common as destinations. It seems that there are some areas, where more cars end their trip, both during the morning and afternoon peak hours, which might cause more congestion during these hours. Comparison with the existing infrastructure of public transport and bike lanes shows no coherence between poor infrastructure for transportation alternatives and common destinations.