TY - JOUR A1 - Knöttner, Julia A1 - Rosenbaum, Dominik A1 - Kurz, Franz A1 - Brunn, Ansgar A1 - Reinartz, Peter T1 - Rule-Based Mapping of Parked Vehicles using Aerial Image Sequences JF - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences N2 - Mapping of parking spaces in cities is a prerequisite for future applications in parking space management like community-based parking. Although terrestrial or vehicle based sensors will be the favorite data source for parking space mapping, airborne monitoring can play a role in building up city wide basis maps which include also parking spaces on ancillary and suburban roads. We present a novel framework for automatic city wide classification of vehicles in moving, stopped and parked using aerial image sequences and information from a road database. The time span of observation of a specific vehicle during an image sequence is usually not long enough to decide unambiguously, whether a vehicle stopped e.g. before a traffic light or is parking along the road. Thus, the workflow includes a vehicle detection and tracking method as well as a rule-based fuzzy-logic workflow for the classification of vehicles. The workflow classifies stopped and parked vehicles by including the neighbourhood of each vehicle via a Delaunay-Graph. The presented method reaches correctness values of around 86.3%, which is demonstrated using three different aerial image sequences. The results depend on several factors like detection quality and road database accuracy. KW - Aerial Image Sequences KW - Vehicle Detection KW - Vehicle Tracking KW - Parking Space Mapping KW - Fuzzy Logic Y1 - 2019 U6 - https://doi.org/doi.org/10.5194/isprs-annals-IV-2-W7-95-2019 VL - IV-2/W7 SP - 95 EP - 101 ER -