This thesis deals with the evaluation of different methods for the quantification of car parking spaces in Vienna's urban street space. The aim of the thesis was to compare the accuracy and efficiency of five survey methods: manual counting on site (ground truth data), GIS-based analysis of the multi-purpose area map (Flächenmehrzweckkarte der Stadt Wien), documentation of the parking schema on site, counting using 2D aerial images and counting in the 3D view of Google Maps.Parts of Vienna's 8th and 19th districts were selected as the study area, as they have different urban structures. The method included the use of QGIS and Python to analyse the GIS data, the creation of a parking schema for systematic categorisation and the calculation of parking spaces based on street lengths and parking types. Participants were involved to count the car parking spaces in the aerial images and to document the parking schemes. The results of each method were analysed and compared with each other to assess their accuracy and applicability.The ground truth data served as a reference for the comparison of the other methods and was considered as the actual number of car parking spaces. Compared to the other methods, the 3D view achieved the lowest deviations (average 19.71% and median 6.06%). While the 2D aerial image count was slightly behind with an average deviation of 24.90% and a median of 9.52%, the GIS method showed the largest deviations (average 29.54% and median 17.66%). The number of parking spaces was also calculated using the documented parking schema. Here, the accuracy of the results depended heavily on the calculation method.The work provides important insights into the advantages and disadvantages of different methods for parking space counting and presents practical ideas for improvement that can be helpful in specific areas of application such as urban planning.