Where’s the Ticket? Identifying Spatio-Temporal Patterns of Parking Violations with Crowdsourced Web-GIS Data

Illegal parking is a widespread issue in urban environments, leading to significant adverse effects on traffic flow, public safety, and the aesthetics of streetscapes. This paper introduces an innovative methodology for the identification and analysis of illegal parking hotspots. To achieve this, a custom Web-GIS platform is developed that employs crowdsourcing, enabling citizens to report the precise locations and types of parking violations they encounter. The platform collects this data, which is then analyzed using a Spatio-Temporal Density Based Spatial Clustering of Applications with Noise (ST-DBSCAN) algorithm. The methodology was applied in the city of Athens, Greece, with the findings revealing that parking violations are not uniformly distributed but instead show distinct spatial and temporal patterns. Specifically, certain areas and times during the day exhibit considerably higher levels of illegal parking. For instance, commercial areas tend to experience more violations during business hours, while residential areas see more issues during evenings and weekends, mainly due to an increasing number of already parked cars and a lack of organized parking spaces. By providing a data-driven approach to identifying critical areas of illegal parking, city officials can better allocate enforcement resources and develop targeted strategies to mitigate this issue, highlighting the significant implications of the study for urban management and policy-making. Therefore, the main goal of this research is to contribute to the enhancement of urban mobility and the overall quality of life by addressing one of the most persistent challenges in city management.