Location-based services and data mining algorithms analyzing objects moving on a complex traffic network are becoming increasingly important. In this paper, we introduce a new approach which effectively and efficiently detects dense areas in spatial networks. In an offline phase, we generate a hierarchical partitioning of the traffic network. Thereby, static entities like roads and buildings are likely to be in the same partitioning if they are close to each other according to their network distance. In the online phase, our prototype ViEWNet allows the effective and efficient monitoring of objects moving on a spatial network. Based on a clear visualization of the traffic intensity in each network cell, the user can easily detect hierarchies of dense areas by our powerful prototype ViEWNet.