There are today many available datasets and methods that can be used to create 3D city models, which in turn can be used for numerous applications within the fields of visualization, communication and analysis. The purpose of this thesis is to perform a practical comparison between three methods for 3D city modeling using different combinations of datasets; one using LiDAR data combined with oriented aerial images, one using only oriented aerial images and one using non-oriented aerial images. In all three cases, geometry and textures are derived from the data and the models are imported into the game engine Unity. The three methods are evaluated in terms of the resulting model, the amount of manual work required and the time consumed as well as the cost of data and software licenses. An application example visualizing flooding scenarios in central Stockholm is featured in the thesis to give a simple demonstration of what can be done with 3D city models in a game engine environment. The result of the study shows that combining LiDAR data with oriented images and using a more manual process to create the model gives a higher potential for the result, both in terms of visual appearance and semantic depth. Using only oriented images and commercial software is the easiest and most reliable way to create a usable 3D city model. Non-oriented images and open-source software can be used for 3D reconstruction but is not suited for larger areas or geographic applications. Finding reliable automatic or semi-automatic methods to create semantically rich 3D city models from remote sensed data would be hugely beneficial, as more sophisticated applications could be programmed with the 3D city model as a base.